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R/plot.misty.object.R
In misty: Miscellaneous Functions 'T. Yanagida'
Defines functions
plot.misty.object
Documented in
plot.misty.object
#' Plots misty.object object
#'
#' This function plots an \code{misty.object} object.
#'
#' @param x \code{misty.object} object.
#' @param plot see 'Details'.
#' @param bar see 'Details'.
#' @param box see 'Details'.
#' @param violin see 'Details'.
#' @param hist see 'Details'.
#' @param point see 'Details'.
#' @param line see 'Details'.
#' @param ci see 'Details'.
#' @param conf.level see 'Details'.
#' @param adjust see 'Details'.
#' @param jitter see 'Details'.
#' @param density see 'Details'.
#' @param square see 'Details'.
#' @param rotate see 'Details'.
#' @param binwidth see 'Details'.
#' @param bins see 'Details'.
#' @param fill see 'Details'.
#' @param hist.apha see 'Details'.
#' @param tile.alpha see 'Details'.
#' @param violin.alpha see 'Details'.
#' @param violin.trim see 'Details'.
#' @param box.width see 'Details'.
#' @param box.alpha see 'Details'.
#' @param linetype see 'Details'.
#' @param linewidth see 'Details'.
#' @param line.col see 'Details'.
#' @param intercept see 'Details'.
#' @param density.col see 'Details'.
#' @param density.linewidth see 'Details'.
#' @param density.linetype see 'Details'.
#' @param point.size see 'Details'.
#' @param point.linewidth see 'Details'.
#' @param point.linetype see 'Details'.
#' @param point.shape see 'Details'.
#' @param point.col see 'Details'.
#' @param ci.col see 'Details'.
#' @param ci.linewidth see 'Details'.
#' @param ci.linetype see 'Details'.
#' @param errorbar.width see 'Details'.
#' @param dodge.width see 'Details'.
#' @param jitter.size see 'Details'.
#' @param jitter.width see 'Details'.
#' @param jitter.height see 'Details'.
#' @param jitter.alpha see 'Details'.
#' @param gray see 'Details'.
#' @param start see 'Details'.
#' @param end see 'Details'.
#' @param color see 'Details'.
#' @param xlab see 'Details'.
#' @param ylab see 'Details'.
#' @param xlim see 'Details'.
#' @param ylim see 'Details'.
#' @param xbreaks see 'Details'.
#' @param ybreaks see 'Details'.
#' @param axis.title.size see 'Details'.
#' @param axis.text.size see 'Details'.
#' @param strip.text.size see 'Details'.
#' @param title see 'Details'.
#' @param subtitle see 'Details'.
#' @param group.col see 'Details'.
#' @param plot.margin see 'Details'.
#' @param legend.title see 'Details'.
#' @param legend.position see 'Details'.
#' @param legend.box.margin see 'Details'.
#' @param legend.key.size see 'Details'.
#' @param legend.text.size see 'Details'.
#' @param facet.ncol see 'Details'.
#' @param facet.nrow see 'Details'.
#' @param facet.scales see 'Details'.
#' @param filename a character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave}
#' function. Note that one of \code{".eps"}, \code{".ps"},
#' \code{".tex"}, \code{".pdf"} (default), \code{".jpeg"},
#' \code{".tiff"}, \code{".png"}, \code{".bmp"},
#' \code{".svg"} or \code{".wmf"} needs to be specified
#' as file extension in the \code{file} argument.
#' @param width a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' @param height a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' @param units a character string indicating the \code{units} argument
#' in the \code{ggsave} function. Note that one of
#' \code{"in"}, \code{"cm"}, \code{"mm"}, or \code{"px"}
#' needs to be specified.
#' @param dpi a numeric value indicating the \code{dpi} argument
#' for the \code{ggsave} function.
#' @param check logical: if \code{TRUE} (default), argument specification
#' is checked.
#' @param ... further arguments passed to or from other methods.
#'
#' @details
#' \describe{
#' This function provides plotting arguments depending on the type of the output
#' object specified for the argument \code{x}:
#' \item{\strong{Output object from \code{aov.b}, \code{aov.w}, and \code{test.welch}}
#' Function}{The \code{plot} function for the misty object of type \code{"aov.b"},
#' \code{"aov.w"}, and \code{test.welch} has following plotting arguments:
#' \itemize{
#' \item{\code{bar}}: logical: if \code{TRUE} (default), bars representing means
#' for each groups are drawn. Note that this argument is only available for the
#' misty object of type \code{"aov.b"} and \code{"test.welch"}.
#' \item{\code{point}}: logical: if \code{TRUE}, points representing means for
#' each groups are drawn.
#' \item{\code{line}}: logical: if \code{TRUE} (default), a line connecting
#' means of each groups and lines connecting data points are drawn
#' when \code{jitter = TRUE}. Note that this argument is only available for
#' misty object of type \code{"aov.w"}.
#' \item{\code{ci}}: logical: if \code{TRUE} (default), error bars representing
#' confidence intervals are drawn.
#' \item{\code{jitter}}: jittered data points are drawn. Note that subject-specific
#' lines are also drawn for the \code{"aov.w"} function when \code{line = TRUE}.
#' \item{\code{conf.level}}: a numeric value between 0 and 1 (default: 0.95)
#' indicating the confidence level of the interval.
#' \item{\code{adjust}}: logical: if \code{TRUE} (default), difference-adjustment
#' for the confidence intervals in a two-sample design is applied.
#' \item{\code{point.size}}: a numeric value indicating the \code{size} (default:
#' \code{3}) aesthetic for the point representing the mean value.
#' \item{\code{line.width}}: a numeric value (default: \code{0.5}) indicating
#' the \code{linewidth} aesthetic for the line connecting means of each Groups.
#' Note that this argument is only available for the \code{"aov.w"} function.
#' \item{\code{errorbar.width}}: a numeric value (default: \code{0.1}) indicating
#' the horizontal bar width of the error bar.
#' \item{\code{jitter.size}}: a numeric value (default: \code{1.25}) indicating
#' the \code{size} aesthetic for the jittered data points.
#' \item{\code{jitter.width}}: a numeric value (default: \code{0.05}) indicating
#' the amount of horizontal jitter.
#' \item{\code{jitter.height}}: a numeric value (default: \code{0}) indicating
#' the amount of vertical jitter.
#' \item{\code{jitter.alpha}}: a numeric value between 0 and 1 (default: \code{0.1})
#' for specifying the \code{alpha} argument in the \code{geom_jitter} function
#' for controlling the opacity of the jittered data points.
#' \item{\code{xlab}}: a character string (default: \code{NULL}) specifying the
#' labels for the x-axis.
#' \item{\code{ylab}}: a character string (default: \code{"y"}) specifying the
#' labels for the y-axis.
#' \item{\code{ylim}}: a numeric vector of length two (default: \code{NULL})
#' specifying limits of the limits of the y-axis.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()}) specifying
#' the points at which tick-marks are drawn at the y-axis.
#' \item{\code{title}}: a character string (default: \code{""}) specifying the
#' text for the title for the plot.
#' \item{\code{subtitle}}: a character string (default: \code{"Two-Sided Confidence Interval"}
#' when \code{adjust = FALSE} or \code{"Two-Sided Difference-Adjusted Confidence Interval"}
#' for the \code{aov.b} function and
#' \code{"Two-Sided Difference-Adjusted Cousineau-Morey Confidence Interval Confidence Interval"}
#' for the \code{aov.w} function when \code{adjust = TRUE}) specifying the text
#' for the subtitle for the plot.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' \item{\strong{Output object from \code{ci.*} Functions}}{The \code{plot}
#' function for the misty object of type \code{"ci.cor"}, \code{"ci.mean"},
#' \code{"ci.median"}, \code{"ci.prop"}, \code{"ci.var"}, and \code{"ci.sd"} has
#' following plotting arguments:
#' \itemize{
#' \item{\code{plot}}: a character string indicating the type of the plot
#' to display, i.e., \code{"ci"} (default) for displaying confidence intervals
#' or \code{"boot"} for displaying bootstrap samples with histograms and density
#' curves when the argument.
#' \item{\code{hist}}: logical: if \code{TRUE} (default), histograms are
#' drawn when \code{plot = "boot"}.
#' \item{\code{density}}: logical: if \code{TRUE} (default), density curves are
#' drawn when \code{plot = "boot"}.
#' \item{\code{point}}: logical: if \code{TRUE} (default), vertical lines
#' representing the point estimate are drawn when \code{plot = "boot"}.
#' \item{\code{ci}}: logical: if \code{TRUE} (default), vertical lines
#' representing the bootstrap confidence intervals are drawn when \code{plot = "boot"}.
#' \item{\code{line}}: logical: if \code{TRUE} (default), a horizontal line
#' is drawn when \code{plot = "ci"} or a vertical line is drawn when
#' \code{plot = "boot"}.
#' \item{\code{point.size}}: a numeric value (default: \code{2.5}) indicating
#' the \code{size} argument in the \code{geom_point} function for controlling
#' the size of points when plotting confidence intervals (\code{plot = "ci"}).
#' \item{\code{point.shape}}: a numeric value between 0 and 25 (default: \code{19})
#' or a character string as plotting symbol indicating the \code{shape} argument
#' in the \code{geom_point} function for controlling the symbols of points
#' when plotting confidence intervals (\code{plot = "ci"}).
#' \item{\code{errorbar.width}}: a numeric value (default: \code{0.3}) indicating
#' the \code{width} argument in the \code{geom_errorbar} function for controlling
#' the width of the whiskers in the \code{geom_errorbar} function when plotting
#' confidence intervals (\code{plot = "ci"}).
#' \item{\code{dodge.width}}: a numeric value (default: \code{0.5}) indicating
#' the \code{width} argument controlling the width of the \code{geom} elements
#' to be dodged when specifying a grouping variable using the argument \code{group}
#' when plotting confidence intervals (\code{plot = "ci"}).
#' \item{\code{binwidth}}: a numeric value or a function (default: \code{NULL})
#' for specifying the \item{\code{bins}}: a numeric value for specifying the
#' \code{bins} argument in the \code{geom_histogram} function for controlling
#' the number of bins when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{hist.alpha}}: a numeric value between 0 and 1 (default: \code{0.4})
#' for specifying the \code{alpha} argument in the \code{geom_histogram}
#' function for controlling the opacity of the bars when plotting bootstrap
#' samples (\code{plot = "boot"}).
#' \item{\code{fill}}: a character string (default: \code{"gray85"}) specifying
#' the \code{fill} argument in the \code{geom_histogram} function controlling
#' the fill aesthetic when plotting bootstrap samples (\code{plot = "boot"}).
#' Note that this argument applied only when no grouping variable was specified
#' \code{group = NULL}.
#' \item{\code{density.col}}: a character string (default: \code{"#0072B2"})
#' specifying the \code{color} argument in the \code{geom_density} function
#' controlling the color of the density curves when plotting bootstrap samples
#' (\code{plot = "boot"}). Note that this argument applied only when no grouping
#' variable was specified \code{group = NULL}.
#' \item{\code{density.linewidth}}: a numeric value (default: \code{0.5}) specifying
#' the \code{linewidth} argument in the \code{geom_density} function controlling
#' the line width of the density curves when plotting bootstrap samples
#' (\code{plot = "boot"}).
#' \item{\code{density.linetype}}: a numeric value or character string (default:
#' \code{0.5}) specifying the \code{linetype} argument in the \code{geom_density}
#' function controlling the line type of the density curves when plotting
#' bootstrap samples (\code{plot = "boot"}).
#' \item{\code{point.col}}: a character string (default: \code{"#CC79A7"}) specifying
#' the \code{color} argument in the \code{geom_vline} function for controlling
#' the color of the vertical line displaying the point estimate when plotting
#' bootstrap samples (\code{plot = "boot"}). Note that this argument applied
#' only when no grouping variable was specified \code{group = NULL}.
#' \item{\code{point.linewidth}}: a numeric value (default: \code{0.6}) specifying
#' the \code{linewdith} argument in the \code{geom_vline} function for
#' controlling the line width of the vertical line displaying the point estimate
#' when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{point.linetype}}: a numeric value or character string (default:
#' \code{"solid"}) specifying the \code{linetype} argument in the \code{geom_vline}
#' function controlling the line type of the vertical line displaying the
#' point estimate when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{ci.col}}: character string (default: \code{"black"}) specifying the
#' \code{color} argument in the \code{geom_vline} function for controlling the
#' color of the vertical line displaying bootstrap confidence intervals when
#' plotting bootstrap samples (\code{plot = "boot"}). Note that this argument
#' applied only when no grouping variable was specified \code{group = NULL}.
#' \item{\code{ci.linewidth}}: a numeric value (default: \code{0.6}) specifying
#' the \code{linewdith} argument in the \code{geom_vline} function for controlling
#' the line width of the vertical line displaying bootstrap confidence intervals
#' when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{ci.linetype}}: a numeric value or character string (default:
#' \code{"dashed"}) specifying the \code{linetype} argument in the \code{geom_vline}
#' function controlling the line type of the vertical line displaying bootstrap
#' confidence intervals when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{intercept}}: a numeric value (default = \code{0}) indicating the
#' \code{yintercept} or \code{xintercept} argument in the \code{geom_hline}
#' or \code{geom_vline} function controlling the position of the horizontal
#' or vertical line when \code{plot = "ci"} and \code{line = TRUE} or when
#' \code{plot = "boot"} and \code{line = TRUE}.
#' \item{\code{linetype}}: a character string (default: \code{"solid"}) indicating
#' the \code{linetype} argument in the \code{geom_hline} or \code{geom_vline}
#' function controlling the line type of the horizontal or vertical line
#' \item{\code{line.col}}: a character string (default: \code{"gray65"}) indicating
#' the \code{color} argument in the \code{geom_hline} or \code{geom_vline}
#' function for controlling the color of the horizontal or vertical line.
#' \item{\code{xlab}}: a character string indicating the \code{name} argument
#' in the \code{scale_x_continuous} function for labeling the x-axis. The default
#' setting is \code{xlab = NULL} when \code{plot = "ci"} and
#' \code{xlab = "Correlation Coefficient"}, \code{xlab = "Arithmetic Mean"},
#' \code{xlab = "Median"}, \code{xlab = "Proportion"}, \code{xlab = "Variance"},
#' or \code{xlab = "Standard Deviation"}.
#' \item{\code{ylab}}: a character string indicating the \code{name} argument
#' in the \code{scale_y_continuous} function for labeling the y-axis. The
#' default setting is \code{ylab = "Correlation Coefficient"}, \code{ylab = "Arithmetic Mean"},
#' \code{ylab = "Median"}, \code{ylab = "Proportion"}, \code{ylab = "Variance"},
#' or \code{ylab = "Standard Deviation"} when \code{plot = "ci"} and
#' \code{ylab = "Probability Density f(x)"} when \code{plot = "boot"}.
#' \item{\code{xlim}}: a numeric vector with two elements indicating the
#' \code{limits} argument in the \code{scale_x_continuous} function for controlling
#' the scale range of the x-axis. The default setting is \code{xlim = NULL}
#' when \code{plot = "ci"} and \code{xlim = c(-1, 1)} for the correlation
#' coefficient and proportion or \code{xlim = NULL) for the arithmetic mean,
#' median, variance and standard deviation when \code{plot = "boot"}.
#' \item{\code{ylim}}: a numeric vector with two elements indicating the
#' \code{limits} argument in the \code{scale_y_continuous} function for controlling
#' the scale range of the y-axis. The default setting is \code{ylim = c(-1, 1)}
#' fpr the correlation coefficient and proportion and \code{ylim = NULL} for
#' the arithmetic mean, median, variance and standard deviation when \code{plot = "ci"}
#' and \code{xlim = NULL} when \code{plot = "boot"}.
#' \item{\code{xbreaks}}: a numeric vector (default: \code{waiver()) indicating
#' the \code{breaks} argument in the \code{scale_x_continuous} function for
#' controlling the x-axis breaks.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()) indicating
#' the \code{breaks} argument in the \code{scale_y_continuous} function for
#' controlling the y-axis breaks.
#' \item{\code{axis.title.size}}: a numeric value (default: \code{11}) indicating
#' the \code{size} argument in the \code{element_text} function for specifying
#' the function controlling the font size of the axis title, i.e.
#' \code{theme(axis.title = element_text(size = axis.text.size))}
#' \item{\code{axis.text.size}}: a numeric value (default: 10) indicating the
#' \code{size} argument in the \code{element_text} function for specifying the
#' function controlling the font size of the axis text,
#' i.e. \code{theme(axis.text = element_text(size = axis.text.size))}.
#' \item{\code{strip.text.size}}: a numeric value (default: \code{11}) indicating
#' the \code{size} argument in the \code{element_text} function for specifying
#' the function controlling the font size of the strip text, i.e.
#' \code{theme(strip.text = element_text(size = strip.text.size))}.
#' \item{\code{title}}: a character string (default: \code{NULL}) indicating the
#' \code{title} argument in the \code{labs} function for the subtitle of the
#' plot.
#' \item{\code{subtitle}}: a character string (default: \code{NULL}) indicating
#' the \code{subtite} argument in the \code{labs} function for the subtitle of
#' the plot.
#' \item{\code{group.col}}: a character vector (default: \code{NULL}) indicating
#' the \code{color} argument in the \code{scale_color_manual} and \code{scale_fill_manual}
#' functions when specifying a grouping variable using the argument \code{group}.
#' \item{\code{plot.margin}}: a numeric vector (default: \code{NA}) with four
#' elements indicating the \code{plot.margin} argument in the \code{theme} function
#' controlling the plot margins. The default setting is \code{c(5.5, 5.5, 5.5, 5.5)}
#' but switches to \code{c(5.5, 5.5, -2.5, 5.5)} when specifying a grouping
#' variable using the argument \code{group}.
#' \item{\code{legend.title}}: a character string (default: \code{""}) indicating
#' the \code{color} argument in the \code{labs} function for specifying the
#' legend title when specifying a grouping variable using the argument \code{group}.
#' \item{\code{legend.position}}: a character string (default: \code{"bottom"})
#' indicating the \code{legend.position} in the \code{theme} argument for
#' controlling the position of the legend function when specifying a
#' grouping variable using the argument \code{group}.
#' \item{\code{legend.box.margin}}: a numeric vector (default: \code{c(-10, 0, 0, 0)})
#' with four elements indicating the \code{legend.box.margin} argument in the
#' \code{theme} function for controlling the margins around the full legend
#' area when specifying a grouping variable using the argument \code{group}.
#' \item{\code{facet.ncol}}: a numeric value (default: \code{NULL}) indicating the
#' \code{ncol} argument in the \code{facet_wrap} function for controlling the
#' number of columns when specifying a split variable using the argument \code{split}.
#' \item{\code{facet.nrow}}: a numeric value (default: \code{NULL}) indicating the
#' \code{nrow} argument in the \code{facet_wrap} function for controlling the
#' number of rows when specifying a split variable using the argument \code{split}.
#' \item{\code{facet.scales}}: a character string (default: \code{"free_y"}) indicating
#' the \code{scales} argument in the \code{facet_wrap} function for controlling the
#' scales shared across facets i.e. \code{"fixed"}, \code{"free_x"},
#' \code{"free_y"} (default) or \code{"free"} when specifying a split variable
#' using the argument \code{split}.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' \item{\strong{Output object from \code{test.levene} Function}}{The \code{plot}
#' function for the misty object of type \code{"test.levene"} has following plotting
#' arguments:
#' \itemize{
#' \item{\code{violin.alpha}}: a numeric value between 0 and 1 (default: \code{0.3})
#' for specifying the \code{alpha} argument in the \code{geom_violin} function
#' for controlling the opacity of the violins.
#' \item{\code{violin.trim}}: logical: if \code{TRUE} (default: \code{FALSE}),
#' the tails of the violins to the range of the data is trimmed.
#' \item{\code{box.alpha}}: a numeric value between 0 and 1 (default: \code{0.2})
#' for specifying the \code{alpha} argument in the \code{geom_boxplot} function
#' for controlling the opacity of the boxplots.
#' \item{\code{box.width}}: a numeric value between 0 and 1 (default: \code{0.2})
#' for specifying the \code{alpha} argument in the \code{geom_boxplot} function
#' for controlling the opacity of the boxplots.
#' \item{\code{jitter.size}}: a numeric value (default: \code{1.25}) indicating
#' the \code{size} aesthetic for the jittered data points.
#' \item{\code{jitter.width}}: a numeric value (default: \code{0.05}) indicating
#' the amount of horizontal jitter.
#' \item{\code{jitter.height}}: a numeric value (default: \code{0}) indicating
#' the amount of vertical jitter.
#' \item{\code{jitter.alpha}}: a numeric value between 0 and 1 (default: \code{0.2})
#' for specifying the \code{alpha} argument in the \code{geom_jitter} function
#' for controlling the opacity of the jittered data points.
#' \item{\code{start}}: a numeric value between 0 and 1 (default: \code{0.9}),
#' graphical parameter to specify the gray value at the low end of the palette.
#' \item{\code{end}}: a numeric value between 0 and 1 (default: \code{0.4}),
#' graphical parameter to specify the gray value at the high end of the palette.
#' \item{\code{color}}: a character vector (default: \code{NULL}), indicating
#' the color of the violins and the boxes. By default, default ggplot2 colors
#' are used.
#' \item{\code{xlab}}: a character string (default: \code{NULL}) specifying
#' the labels for the x-axis.
#' \item{\code{ylab}}: a character string (default: \code{NULL}) specifying
#' the labels for the y-axis.
#' \item{\code{ylim}}: a numeric vector (default: \code{NULL}) of length two specifying
#' limits of the limits of the y-axis.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()})
#' specifying the points at which tick-marks are drawn at the y-axis.
#' \item{\code{title}}: a character string (default: \code{""}) specifying the
#' text for the title for the plot.
#' \item{\code{subtitle}}: a character string (default: \code{""}) specifying
#' the text for the subtitle for the plot.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' \item{\strong{Output object from \code{test.t} and \code{test.z}}}{The \code{plot}
#' function for the misty object of type \code{"test.t"} and \code{"test.z"} has
#' following plotting arguments:
#' \itemize{
#' \item{\code{bar}}: logical: if \code{TRUE} (default), bars representing means
#' for each groups are drawn.
#' \item{\code{point}}: logical: if \code{TRUE}, points representing means for
#' each groups are drawn.
#' \item{\code{ci}}: logical: if \code{TRUE} (default), error bars representing
#' confidence intervals are drawn.
#' \item{\code{jitter}}: logical: if \code{TRUE}, jittered data points are drawn.
#' \item{\code{line}}: logical: if \code{TRUE} (default), a horizontal line is
#' drawn at \code{mu} for the one-sample t- or z-test or at 0 for the paired-sample
#' t- or z-test.
#' \item{\code{conf.level}}: a numeric value between 0 and 1 (default: 0.95)
#' indicating the confidence level of the interval.
#' \item{\code{adjust}}: logical: if \code{TRUE} (default), difference-adjustment
#' for the confidence intervals in a two-sample design is applied.
#' \item{\code{point.size}}: a numeric value indicating the \code{size} (default:
#' \code{3}) aesthetic for the point representing the mean value.
#' \item{\code{errorbar.width}}: a numeric value (default: \code{0.1}) indicating
#' the horizontal bar width of the error bar.
#' \item{\code{linetype}}: an integer value or character string (default: \code{3})
#' specifying the line type for the line representing the population mean under
#' the null hypothesis, i.e., 0 = blank, 1 = solid, 2 = dashed, 3 = dotted,
#' 4 = dotdash, 5 = longdash, or 6 = twodash.
#' \item{\code{linewidth}}: a numeric value indicating the \code{linewidth}
#' (default: \code{0.8} aesthetic for the line representing the population mean
#' under the null hypothesis.
#' \item{\code{jitter.size}}: a numeric value (default: \code{1.25}) indicating
#' the \code{size} aesthetic for the jittered data points.
#' \item{\code{jitter.width}}: a numeric value (default: \code{0.05}) indicating
#' the amount of horizontal jitter.
#' \item{\code{jitter.height}}: a numeric value (default: \code{0}) indicating
#' the amount of vertical jitter.
#' \item{\code{jitter.alpha}}: a numeric value between 0 and 1 (default: \code{0.1})
#' for specifying the \code{alpha} argument in the \code{geom_jitter} function
#' for controlling the opacity of the jittered data points.
#' \item{\code{xlab}}: a character string (default: \code{NULL}) specifying the
#' labels for the x-axis.
#' \item{\code{ylab}}: a character string (default: \code{"y"}) specifying the
#' labels for the y-axis.
#' \item{\code{ylim}}: a numeric vector of length two (default: \code{NULL})
#' specifying limits of the limits of the y-axis.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()}) specifying
#' the points at which tick-marks are drawn at the y-axis.
#' \item{\code{title}}: a character string (default: \code{""}) specifying the
#' text for the title for the plot.
#' \item{\code{subtitle}}: a character string (default: \code{"Two-Sided Confidence Interval"}
#' when \code{adjust = FALSE} or \code{"Two-Sided Difference-Adjusted Confidence Interval"}
#' when \code{adjust = TRUE}) specifying the text for the subtitle for the plot.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' }
#'
#' @author
#' Takuya Yanagida \email{takuya.yanagida@@univie.ac.at}
#'
#' @method plot misty.object
#'
#' @export
plot.misty.object <- function(x, plot = x$args$plot, bar = x$args$bar,
box = x$args$box, violin = x$args$violin,
hist = x$args$hist,point = x$args$point,
line = x$args$line, ci = x$args$ci,
conf.level = x$args$conf.level, adjust = x$args$adjust,
jitter = x$args$jitter, density = x$args$density,
square = x$args$square, rotate = x$args$rotate,
binwidth = x$args$binwidth, bins = x$args$bins,
fill = x$args$fill, hist.alpha = x$args$hist.alpha,
tile.alpha = x$args$tile.alpha, violin.alpha = x$args$violin.alpha,
violin.trim = x$args$violin.trim, box.width = x$args$box.width,
box.alpha = x$args$box.alpha, linetype = x$args$linetype,
linewidth = x$args$linewidth, line.col = x$args$line.col,
intercept = x$args$intercept, density.col = x$args$density.col,
density.linewidth = x$args$density.linewidth,
density.linetype = x$args$density.linetype,
point.size = x$args$point.size,
point.linewidth = x$args$point.linewidth,
point.linetype = x$args$point.linetype,
point.shape = x$args$point.shape,
point.col = x$args$point.col, ci.col = x$args$ci.col,
ci.linewidth = x$args$ci.linewidth, ci.linetype = x$args$ci.linetype,
errorbar.width = x$args$errorbar.width, dodge.width = x$args$dodge.width,
jitter.size = x$args$jitter.size, jitter.width = x$args$jitter.width,
jitter.height = x$args$jitter.height, jitter.alpha = x$args$jitter.alpha,
gray = x$args$gray, start = x$args$start, end = x$args$end,
color = x$args$color, xlab = x$args$xlab, ylab = x$args$ylab,
xlim = x$args$xlim, ylim = x$args$ylim, xbreaks = x$args$xbreaks,
ybreaks = x$args$ybreaks, axis.title.size = x$args$axis.title.sizes,
axis.text.size = x$args$axis.text.size, strip.text.size = x$args$strip.text.size,
title = x$args$title, subtitle = x$args$subtitle,
group.col = x$args$group.col, plot.margin = x$args$plot.margin,
legend.title = x$args$legend.title, legend.position = x$args$legend.position,
legend.box.margin = x$args$legend.box.margin, legend.key.size = x$args$legend.key.size,
legend.text.size = x$args$legend.text.size, facet.ncol = x$args$facet.ncol,
facet.nrow = x$args$facet.nrow, facet.scales = x$args$facet.scales,
filename = x$args$filename, width = x$args$width, height = x$args$height,
units = x$args$units, dpi = x$args$dpi, check = TRUE, ...) {
#_____________________________________________________________________________
#
# Initial Check --------------------------------------------------------------
# Check if input 'x' is missing or NULL
if (isTRUE(missing(x) || is.null(x))) { stop("Please specify a misty object for the argument 'x'.", call. = FALSE) }
# Check if input 'x' is a misty object
if (isTRUE(!inherits(x, what = "misty.object"))) { stop("Please specify a misty object for the argument 'x'.", call. = FALSE) }
# Check if input 'x' is supported by the function
if (isTRUE(!x$type %in% c("aov.b", "aov.w", "boot.bs", "ci.cor", "ci.mean", "ci.median", "ci.prop", "ci.var", "ci.sd", "item.dfi", "multilevel.r2", "multilevel.r2.manual", "na.pattern", "test.levene", "test.welch", "test.z", "test.t"))) { stop("This type of misty object is not supported by the plot.misty.object() function.", call. = FALSE) }
#_____________________________________________________________________________
#
# Input Check-----------------------------------------------------------------
# Global Variables
group <- id <- low <- m <- m.diff <- m.low <- m.upp <- mu <- n.pattern <- obs_miss <- part <- pattern <- upp <- variable <- NULL
#_____________________________________________________________________________
#
# Between-Subject Analysis of Variance (ANOVA) -------------------------------
switch(x$type, "aov.b" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Means and (Difference-Adjusted) Confidence Intervals by Group ####
ci.table <- misty::ci.mean(x$data, y, group = "group", adjust = adjust, conf.level = conf.level, output = FALSE)$result
#—————————————————————————————————————— # #
### Create ggplot ####
# Subtitle
if (isTRUE(ci)) { if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Interval") } else { subtitle } } else { subtitle <- "" }
p <- ggplot2::ggplot(x$data, ggplot2::aes(group, y)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#—————————————————————————————————————— # #
### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = ci.table, ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#—————————————————————————————————————— # #
### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = ci.table, ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#—————————————————————————————————————— # #
### Points ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = ci.table, ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#—————————————————————————————————————— # #
### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#_____________________________________________________________________________
#
# Repeated Measures Analysis of Variance (Within-Subject ANOVA ---------------
}, "aov.w" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(linewidth)) { linewidth <- 0.5 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Compute Means and (Difference-Adjusted) Confidence Intervals by Group ####
ci.table <- misty::ci.mean.w(x$data$wide, adjust = adjust, conf.level = conf.level, na.omit = x$args$na.omit, check = FALSE, output = FALSE)$result
#—————————————————————————————————————— # #
### Create ggplot ####
# Subtitle
if (isTRUE(ci)) { if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Cousineau-Morey Confidence Interval") } else { subtitle } } else { subtitle <- "" }
p <- ggplot2::ggplot(x$data$long, ggplot2::aes(time, y, group = 1L)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#—————————————————————————————————————— # #
### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = ci.table, ggplot2::aes(variable, m, ymin = low, ymax = upp), width = errorbar.width)) }
#—————————————————————————————————————— # #
### Points ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = ci.table, ggplot2::aes(variable, m), stat = "identity", size = point.size)) }
#—————————————————————————————————————— # #
### Lines ####
if (isTRUE(line)) { p <- p + suppressWarnings(ggplot2::geom_line(data = ci.table, ggplot2::aes(variable, m), stat = "identity", linewidth = linewidth)) }
#—————————————————————————————————————— # #
### Add jittered points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#—————————————————————————————————————— # #
### Individual lines ####
if (isTRUE(jitter && line)) { p <- p + ggplot2::geom_line(data = x$data$long, ggplot2::aes(time, y, group = id), alpha = jitter.alpha, position = ggplot2::position_dodge(jitter.width)) }
#_____________________________________________________________________________
#
# Bollen-Stine Bootstrap with Incomplete Data, boot.bs() ---------------------
}, "boot.bs" = {
chisq <- NULL
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Data ####
plotdat <- data.frame(chisq = x$boot.chisq)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create ggplot ####
p <- ggplot2::ggplot(plotdat, ggplot2::aes(chisq)) +
ggplot2::theme_bw() +
ggplot2::geom_histogram(ggplot2::aes(y = ggplot2::after_stat(density)), color = "black", alpha = 0.4, fill = "gray85") +
ggplot2::geom_density(color = "#0072B2") +
ggplot2::geom_vline(ggplot2::aes(xintercept = x$result$chisq, color = "Observed Test Statistic")) +
ggplot2::scale_x_continuous(name = expression(paste(chi^2, " Test Statistic")), limits = c(0L, max(c(plotdat$chisq, x$result$chisq), na.rm = TRUE))) +
ggplot2::scale_y_continuous(name = "Probability Density, f(x)", expand = ggplot2::expansion(mult = c(0L, 0.05))) +
ggplot2::scale_color_manual(values = c("Observed Test Statistic" = "#CC79A7")) +
ggplot2::theme(legend.position = "bottom",
legend.box.margin = ggplot2::margin(-15L, 0L, 0L, 0L),
legend.title = ggplot2::element_blank(),
legend.background = ggplot2::element_rect(fill = "transparent"))
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Correlation Coefficients --------------
}, "ci.cor" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab', 'ylab', 'xlim' and 'ylim' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Correlation Coefficient" } else { ylab }
ylim <- if (isTRUE(is.null(ylim))) { c(-1, 1) } else { ylim }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Correlation Coefficient" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
xlim <- if (isTRUE(is.null(xlim))) { c(-1, 1) } else { xlim }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Correlation Coefficient with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "cor", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
stop("There are no confidence intervals for the correlation coefficient to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (isTRUE(any(!is.na(x$boot$cor)))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "cor", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
stop("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Arithmetic Means ----------------------
}, "ci.mean" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Arithmetic Mean" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Arithmetic Mean" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Arithmetic Mean with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "m", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
plot <- "none"
warning("There are no confidence intervals for the arithmetic mean to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$m))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "m", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
plot <- "none"
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Median --------------------------------
}, "ci.median" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Arithmetic Mean" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Arithmetic Mean" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Median with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "med", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the median to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$med))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "med", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Proportions ---------------------------
}, "ci.prop" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab', 'ylab', and 'ylim' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Proportion" } else { ylab }
ylim <- if (isTRUE(is.null(ylim))) { c(0, 1) } else { ylim }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Proportion" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
xlim <- if (isTRUE(is.null(xlim))) { c(0, 1) } else { xlim }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Proportion with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "prop", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the proportion to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$prop))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "prop", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Variances -----------------------------
}, "ci.var" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Variance" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Variance" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Variance with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "var", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the variance to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$var))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "var", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Standard Deviations -------------------
}, "ci.sd" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Variance" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Variance" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Standard Deviation with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "sd", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the standard deviation to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$sd))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "sd", group = x$datagroup, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# Dynamic Fit Index Cutoffs --------------------------------------------------
}, "item.dfi" = {
fit <- cutoff <- NULL
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Data ####
#—————————————————————————————————————— #
### Level 0 ####
if (isTRUE(length(x$result$fit.sim) == 1L)) {
df <- data.frame(level = "Level 0", group = "True",
index = factor(rep(c("CFI", "TLI", "RMSEA", "SRMR"), each = x$args$nrep), levels = c("CFI", "TLI", "RMSEA", "SRMR")),
fit = unlist(x$result$fit.sim[["Level 0"]]),
cutoff = rep( unlist(x$result$fit.cutoff["Level 0", c("cfi", "tli", "rmsea", "srmr")]), each = x$args$nrep))
#—————————————————————————————————————— #
### Level 0, 1, 2, and/or 3 ####
} else {
df <- NULL
for (i in setdiff(names(x$result$fit.sim), "Level 0")) {
df <- rbind(df,
data.frame(level = i,
rbind(data.frame(group = "True",
index = factor(rep(c("CFI", "TLI", "RMSEA", "SRMR"), each = x$args$nrep), levels = c("CFI", "TLI", "RMSEA", "SRMR")),
fit = unlist(x$result$fit.sim[["Level 0"]]),
cutoff = rep( unlist(x$result$fit.cutoff["Level 0", c("cfi", "tli", "rmsea", "srmr")]), each = x$args$nrep)),
data.frame(group = "Misspecified",
index = factor(rep(c("CFI", "TLI", "RMSEA", "SRMR"), each = x$args$nrep), levels = c("CFI", "TLI", "RMSEA", "SRMR")),
fit = unlist(x$result$fit.sim[[i]]),
cutoff = rep( unlist(x$result$fit.cutoff[i, c("cfi", "tli", "rmsea", "srmr")]), each = x$args$nrep)))))
}
df$group <- factor(df$group, levels = c("True", "Misspecified"))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot ####
p <- ggplot2::ggplot(df, ggplot2::aes(fit, group = group, color = group, fill = group)) +
ggplot2::theme_bw() +
ggplot2::geom_histogram(position = "identity", color = "gray60", alpha = 0.5) +
ggplot2::geom_vline(ggplot2::aes(xintercept = cutoff, group = group, color = group), linetype = "longdash") +
ggplot2::scale_fill_manual(values = c("#56B4E9", "#E9798C"))+
ggplot2::scale_color_manual(values = c("#56B4E9", "#E9798C"))+
ggplot2::facet_grid(level ~ index, scales = "free_x" ) +
ggplot2::scale_x_continuous(name = "") +
ggplot2::scale_y_continuous(name = "Count", expand = ggplot2::expansion(mult = c(0L, 0.05))) +
ggplot2::theme(legend.position = "bottom",
legend.box.margin = ggplot2::margin(-20L, 0L, 0L, 0L),
legend.title = ggplot2::element_blank(),
legend.background = ggplot2::element_rect(fill = "transparent"),
strip.text = ggplot2::element_text(size = 11))
#_____________________________________________________________________________
#
# R-Squared Measures for Multilevel and LMMs ---------------------------------
}, "multilevel.r2" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Not Cluster-Mean-Centered ####
# Predictors are not cluster-mean-centered
if (isTRUE(ncol(x$result$rs$decomp) == 1L)) {
df <- data.frame(var = factor(rep("Total", times = 4L)),
part = factor(c("Fixed Slopes", "Slope Variation", "Intercept Variation", "Residual"), levels = c("Residual", "Intercept Variation", "Slope Variation", "Fixed Slopes")),
y = as.vector(x$result$rs$decomp))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Cluster-Mean-Centered ####
} else {
df <- data.frame(var = factor(rep(c("Total", "Within", "Between"), each = 5L), levels = c("Total", "Within", "Between")),
part = factor(c("Fixed Slopes (Within)", "Fixed Slopes (Between)","Slope Variation (Within)", "Intercept Variation (Between)", "Residual (Within)"), levels = c("Residual (Within)", "Intercept Variation (Between)", "Slope Variation (Within)", "Fixed Slopes (Between)", "Fixed Slopes (Within)")),
y = as.vector(x$result$rs$decomp))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot ####
p <- ggplot2::ggplot(df, ggplot2::aes(x = var, y = y, fill = part)) +
ggplot2::geom_bar(stat = "identity") +
ggplot2::scale_y_continuous(name = "Proportion of Variance", breaks = seq(0L, 1L, by = 0.1)) +
ggplot2::theme_bw() +
ggplot2::theme(axis.title.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
legend.box.margin = ggplot2::margin(-10L, 6L, 6L, 6L)) +
ggplot2::guides(fill = ggplot2::guide_legend(nrow = 2L, reverse = TRUE))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Gray Color Scales ####
if (isTRUE(gray)) {
p <- p + ggplot2::scale_fill_grey(start = end, end = start)
} else {
p <- p + ggplot2::scale_fill_manual(values = rev(color))
}
#_____________________________________________________________________________
#
# R-Squared Measures for Multilevel and LMMS, Manual Input -------------------
}, "multilevel.r2.manual" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Not Cluster-Mean-Centered ####
# Predictors are not cluster-mean-centered
if (isTRUE(ncol(x$result$decomp) == 1L)) {
df <- data.frame(var = factor(rep("Total", times = 4L)),
part = factor(c("Fixed Slopes", "Slope Variation", "Intercept Variation", "Residual"), levels = c("Residual", "Intercept Variation", "Slope Variation", "Fixed Slopes")),
y = as.vector(x$result$decomp))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Cluster-Mean-Centered ####
} else {
df <- data.frame(var = factor(rep(c("Total", "Within", "Between"), each = 5L), levels = c("Total", "Within", "Between")),
part = factor(c("Fixed Slopes (Within)", "Fixed Slopes (Between)","Slope Variation (Within)", "Intercept Variation (Between)", "Residual (Within)"), levels = c("Residual (Within)", "Intercept Variation (Between)", "Slope Variation (Within)", "Fixed Slopes (Between)", "Fixed Slopes (Within)")),
y = as.vector(x$result$decomp))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot ####
p <- ggplot2::ggplot(df, ggplot2::aes(x = var, y = y, fill = part)) +
ggplot2::geom_bar(stat = "identity") +
ggplot2::scale_y_continuous(name = "Proportion of Variance", breaks = seq(0L, 1L, by = 0.1)) +
ggplot2::theme_bw() +
ggplot2::theme(axis.title.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
legend.box.margin = ggplot2::margin(-10L, 6L, 6L, 6L)) +
ggplot2::guides(fill = ggplot2::guide_legend(nrow = 2L, reverse = TRUE))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Gray Color Scales ####
if (isTRUE(gray)) {
p <- p + ggplot2::scale_fill_grey(start = end, end = start)
} else {
p <- p + ggplot2::scale_fill_manual(values = rev(color))
}
#_____________________________________________________________________________
#
# Missing Data Pattern ------------------------------------------------------
}, "na.pattern" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Data ####
plotdat <- do.call("rbind", apply(x$result[-nrow(x$result), c("pattern", colnames(x$data))], 1, function(y) {
data.frame(pattern = y["pattern"], var = colnames(x$data), obs_miss = y[colnames(x$data)], x = seq_len(ncol(x$data)), row.names = NULL)
}))
# Factor
plotdat$obs_miss <- factor(ifelse(plotdat$obs_miss == 1L, "Observed", "Missing"))
# Patterns excluded
if (isTRUE(!is.null(x$args$n.pattern))) {
n.pattern.exclude <- names(which(table(apply(is.na(x$data), 1L, function(y) paste(as.numeric(y), collapse = ""))) < x$args$n.pattern))
} else {
n.pattern.exclude <- NULL
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create ggplot ####
p <- ggplot2::ggplot(plotdat, ggplot2::aes(x, pattern, fill = obs_miss, alpha = tile.alpha)) +
ggplot2::geom_tile(color = "black") +
ggplot2::scale_fill_manual(values = c("Missing" = color[1L], "Observed" = color[2L])) +
ggplot2::scale_alpha_continuous(limits = c(0, 1), guide = "none") +
ggplot2::scale_x_continuous("Number of Missing Entries per Variable",
breaks = seq_len(length(colnames(x$data))),
labels = as.character(x$result[nrow(x$result), colnames(x$data)]),
sec.axis = ggplot2::dup_axis(labels = colnames(x$data), name = "Variable")) +
ggplot2::scale_y_reverse("Pattern Frequency",
breaks = seq_len(length(x$result$n) - 1L), labels = x$result[-nrow(x$result), "n"],
sec.axis = ggplot2::dup_axis(labels = x$result[-nrow(x$result), "nNA"], name = "Number of Missing Entries per Pattern")) +
ggplot2::theme(plot.margin = ggplot2::margin(t = plot.margin[1L], r = plot.margin[2L], b = plot.margin[3L], l = plot.margin[4L]),
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
legend.key.size = ggplot2::unit(legend.key.size, "pt"),
legend.text = ggplot2::element_text(size = legend.text.size),
legend.box.margin = ggplot2::margin(t = legend.box.margin[1L], r = legend.box.margin[2L], b = legend.box.margin[3L], l = legend.box.margin[4L]),
panel.grid.minor = ggplot2::element_blank(), panel.grid.major = ggplot2::element_blank())
### Square Plot Tiles ####
if (isTRUE(square)) { p <- p + ggplot2::coord_fixed(expand = FALSE) } else { p <- p + ggplot2::coord_cartesian(expand = FALSE) }
### Rotate Labels ####
if (isTRUE(rotate)) { p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90L)) }
### Caption ####
if (isTRUE(length(n.pattern.exclude) != 0L)) {
p <- p + ggplot2::labs(caption = paste0("Note. ", length(n.pattern.exclude), ifelse(length(n.pattern.exclude) == 1L, " pattern ", " patterns "), " with less than ", n.pattern, " cases removed.")) +
ggplot2::theme(plot.caption = ggplot2::element_text(hjust = 0.5, vjust = 5))
}
#_____________________________________________________________________________
#
# Levene's Test for Homogeneity of Variance ----------------------------------
}, "test.levene" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(violin.alpha)) { violin.alpha <- 0.3 }
if (is.null(violin.trim)) { violin.trim <- FALSE }
if (is.null(box.alpha)) { box.alpha <- 0.2 }
if (is.null(box.width)) { box.width <- 0.2 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(gray)) { gray <- FALSE }
if (is.null(start)) { start <- 0.9 }
if (is.null(end)) { end <- 0.4 }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create Plot ####
p <- ggplot2::ggplot(x$data, ggplot2::aes(group, y, fill = group)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5),
plot.title = ggplot2::element_text(hjust = 0.5)) +
ggplot2::guides(fill = "none")
# Add violin plots
if (isTRUE(violin)) { p <- p + ggplot2::geom_violin(alpha = violin.alpha, trim = violin.trim) }
# Add boxplots
if (isTRUE(box)) { p <- p + ggplot2::geom_boxplot(alpha = box.alpha, width = box.width) }
# Add jittered points
if (isTRUE(jitter)) { p <- p + ggplot2::geom_jitter(alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size) }
# Gray color scales
if (isTRUE(gray)) {
p <- p + ggplot2::scale_fill_grey(start = start, end = end)
# User-specified colors
} else {
if (isTRUE(!is.null(color))) { p <- p + ggplot2::scale_fill_manual(values = color) }
}
#_____________________________________________________________________________
#
# t-Test ---------------------------------------------------------------------
}, "test.t" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(linetype)) { linetype <- 3 }
if (is.null(linewidth)) { linewidth <- 0.8 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## One-, Two-, or Paired Sample ####
switch(x$sample,
#—————————————————————————————————————— #
### One-Sample ####
"one" = {
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0, m), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0, m, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(data = data.frame(mu = x$args$mu), ggplot2::aes(yintercept = mu), linetype = linetype, linewidth = linewidth) }
#—————————————————————————————————————— #
### Two-Sample ####
}, "two" = {
# Plot data
plotdat <- split(x$data[, 1L], f = x$data[, 2L]) |> (\(y) data.frame(group = factor(c(rep(x$result[1L, "group"], times = length(y[[1L]])), rep(x$result[2L, "group"], times = length(y[[2L]])))), y = unlist(y)) )()
# Confidence interval
ci.table <- misty::ci.mean(plotdat[, "y"], group = plotdat[, "group"], adjust = adjust, conf.level = conf.level, output = FALSE)$result
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Interval") } else { subtitle }
p <- ggplot2::ggplot(ci.table, ggplot2::aes(group, m)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) + ggplot2::theme_bw() +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = plotdat, ggplot2::aes(x = group, y = y), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#—————————————————————————————————————— #
### Paired-Sample ####
}, "paired" = {
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0, m.diff), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0, m.diff), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0, m.diff, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(yintercept = 0L, linetype = linetype, linewidth = linewidth) }
})
#_____________________________________________________________________________
#
# Welch's Test ---------------------------------------------------------------
}, test.welch = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Means and (Difference-Adjusted) Confidence Intervals by Group ####
ci.table <- x$result$descript
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create ggplot ####
# Subtitle
if (isTRUE(ci)) { if (isTRUE(subtitle == "Confidence Intervals")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Intervals") } else { subtitle } } else { subtitle <- "" }
p <- ggplot2::ggplot(x$data, ggplot2::aes(group, y)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#—————————————————————————————————————— #
### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = ci.table, ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#—————————————————————————————————————— #
### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = ci.table, ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#—————————————————————————————————————— #
### Points ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = ci.table, ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#—————————————————————————————————————— #
### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = x$data, ggplot2::aes(group, y), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#_____________________________________________________________________________
#
# z-Test ---------------------------------------------------------------------
}, "test.z" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(linetype)) { linetype <- 3 }
if (is.null(linewidth)) { linewidth <- 0.8 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## One-, Two-, or Paired Sample ####
switch(x$sample,
#—————————————————————————————————————— #
### One-Sample ####
"one" = {
#···················
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#···················
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0L, m), stat = "summary", fun = "mean")) }
#···················
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0L, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0L, m, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(data = data.frame(mu = x$args$mu), ggplot2::aes(yintercept = mu), linetype = linetype, linewidth = linewidth) }
#—————————————————————————————————————— #
### Two-Sample ####
}, "two" = {
# Plot data
plotdat <- split(x$data[, 1L], f = x$data[, 2L]) |> (\(y) data.frame(group = factor(c(rep(x$result[1L, "group"], times = length(y[[1L]])), rep(x$result[2L, "group"], times = length(y[[2L]])))), y = unlist(y)))()
# Confidence interval
ci.table <- misty::ci.mean(plotdat[, "y"], group = plotdat[, "group"], adjust = adjust, conf.level = conf.level, output = FALSE)$result
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Interval") } else { subtitle }
p <- ggplot2::ggplot(ci.table, ggplot2::aes(group, m)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) + ggplot2::theme_bw() +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = plotdat, ggplot2::aes(x = group, y = y), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#—————————————————————————————————————— #
### Paired-Sample ####
}, "paired" = {
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0L, m.diff), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0L, m.diff), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0L, m.diff, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(yintercept = 0L, linetype = linetype, linewidth = linewidth) }
})
})
#_____________________________________________________________________________
#
# Save Plot ------------------------------------------------------------------
if (isTRUE(!is.null(filename))) { suppressWarnings(suppressMessages(ggplot2::ggsave(filename = filename, plot = p, width = width, height = height, units = units, dpi = dpi))) }
#_____________________________________________________________________________
#
# Plot -----------------------------------------------------------------------
return(p)
}
#_______________________________________________________________________________
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Defines functions plot.misty.object
Documented in plot.misty.object
#' Plots misty.object object
#'
#' This function plots an \code{misty.object} object.
#'
#' @param x \code{misty.object} object.
#' @param plot see 'Details'.
#' @param bar see 'Details'.
#' @param box see 'Details'.
#' @param violin see 'Details'.
#' @param hist see 'Details'.
#' @param point see 'Details'.
#' @param line see 'Details'.
#' @param ci see 'Details'.
#' @param conf.level see 'Details'.
#' @param adjust see 'Details'.
#' @param jitter see 'Details'.
#' @param density see 'Details'.
#' @param square see 'Details'.
#' @param rotate see 'Details'.
#' @param binwidth see 'Details'.
#' @param bins see 'Details'.
#' @param fill see 'Details'.
#' @param hist.apha see 'Details'.
#' @param tile.alpha see 'Details'.
#' @param violin.alpha see 'Details'.
#' @param violin.trim see 'Details'.
#' @param box.width see 'Details'.
#' @param box.alpha see 'Details'.
#' @param linetype see 'Details'.
#' @param linewidth see 'Details'.
#' @param line.col see 'Details'.
#' @param intercept see 'Details'.
#' @param density.col see 'Details'.
#' @param density.linewidth see 'Details'.
#' @param density.linetype see 'Details'.
#' @param point.size see 'Details'.
#' @param point.linewidth see 'Details'.
#' @param point.linetype see 'Details'.
#' @param point.shape see 'Details'.
#' @param point.col see 'Details'.
#' @param ci.col see 'Details'.
#' @param ci.linewidth see 'Details'.
#' @param ci.linetype see 'Details'.
#' @param errorbar.width see 'Details'.
#' @param dodge.width see 'Details'.
#' @param jitter.size see 'Details'.
#' @param jitter.width see 'Details'.
#' @param jitter.height see 'Details'.
#' @param jitter.alpha see 'Details'.
#' @param gray see 'Details'.
#' @param start see 'Details'.
#' @param end see 'Details'.
#' @param color see 'Details'.
#' @param xlab see 'Details'.
#' @param ylab see 'Details'.
#' @param xlim see 'Details'.
#' @param ylim see 'Details'.
#' @param xbreaks see 'Details'.
#' @param ybreaks see 'Details'.
#' @param axis.title.size see 'Details'.
#' @param axis.text.size see 'Details'.
#' @param strip.text.size see 'Details'.
#' @param title see 'Details'.
#' @param subtitle see 'Details'.
#' @param group.col see 'Details'.
#' @param plot.margin see 'Details'.
#' @param legend.title see 'Details'.
#' @param legend.position see 'Details'.
#' @param legend.box.margin see 'Details'.
#' @param legend.key.size see 'Details'.
#' @param legend.text.size see 'Details'.
#' @param facet.ncol see 'Details'.
#' @param facet.nrow see 'Details'.
#' @param facet.scales see 'Details'.
#' @param filename a character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave}
#' function. Note that one of \code{".eps"}, \code{".ps"},
#' \code{".tex"}, \code{".pdf"} (default), \code{".jpeg"},
#' \code{".tiff"}, \code{".png"}, \code{".bmp"},
#' \code{".svg"} or \code{".wmf"} needs to be specified
#' as file extension in the \code{file} argument.
#' @param width a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' @param height a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' @param units a character string indicating the \code{units} argument
#' in the \code{ggsave} function. Note that one of
#' \code{"in"}, \code{"cm"}, \code{"mm"}, or \code{"px"}
#' needs to be specified.
#' @param dpi a numeric value indicating the \code{dpi} argument
#' for the \code{ggsave} function.
#' @param check logical: if \code{TRUE} (default), argument specification
#' is checked.
#' @param ... further arguments passed to or from other methods.
#'
#' @details
#' \describe{
#' This function provides plotting arguments depending on the type of the output
#' object specified for the argument \code{x}:
#' \item{\strong{Output object from \code{aov.b}, \code{aov.w}, and \code{test.welch}}
#' Function}{The \code{plot} function for the misty object of type \code{"aov.b"},
#' \code{"aov.w"}, and \code{test.welch} has following plotting arguments:
#' \itemize{
#' \item{\code{bar}}: logical: if \code{TRUE} (default), bars representing means
#' for each groups are drawn. Note that this argument is only available for the
#' misty object of type \code{"aov.b"} and \code{"test.welch"}.
#' \item{\code{point}}: logical: if \code{TRUE}, points representing means for
#' each groups are drawn.
#' \item{\code{line}}: logical: if \code{TRUE} (default), a line connecting
#' means of each groups and lines connecting data points are drawn
#' when \code{jitter = TRUE}. Note that this argument is only available for
#' misty object of type \code{"aov.w"}.
#' \item{\code{ci}}: logical: if \code{TRUE} (default), error bars representing
#' confidence intervals are drawn.
#' \item{\code{jitter}}: jittered data points are drawn. Note that subject-specific
#' lines are also drawn for the \code{"aov.w"} function when \code{line = TRUE}.
#' \item{\code{conf.level}}: a numeric value between 0 and 1 (default: 0.95)
#' indicating the confidence level of the interval.
#' \item{\code{adjust}}: logical: if \code{TRUE} (default), difference-adjustment
#' for the confidence intervals in a two-sample design is applied.
#' \item{\code{point.size}}: a numeric value indicating the \code{size} (default:
#' \code{3}) aesthetic for the point representing the mean value.
#' \item{\code{line.width}}: a numeric value (default: \code{0.5}) indicating
#' the \code{linewidth} aesthetic for the line connecting means of each Groups.
#' Note that this argument is only available for the \code{"aov.w"} function.
#' \item{\code{errorbar.width}}: a numeric value (default: \code{0.1}) indicating
#' the horizontal bar width of the error bar.
#' \item{\code{jitter.size}}: a numeric value (default: \code{1.25}) indicating
#' the \code{size} aesthetic for the jittered data points.
#' \item{\code{jitter.width}}: a numeric value (default: \code{0.05}) indicating
#' the amount of horizontal jitter.
#' \item{\code{jitter.height}}: a numeric value (default: \code{0}) indicating
#' the amount of vertical jitter.
#' \item{\code{jitter.alpha}}: a numeric value between 0 and 1 (default: \code{0.1})
#' for specifying the \code{alpha} argument in the \code{geom_jitter} function
#' for controlling the opacity of the jittered data points.
#' \item{\code{xlab}}: a character string (default: \code{NULL}) specifying the
#' labels for the x-axis.
#' \item{\code{ylab}}: a character string (default: \code{"y"}) specifying the
#' labels for the y-axis.
#' \item{\code{ylim}}: a numeric vector of length two (default: \code{NULL})
#' specifying limits of the limits of the y-axis.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()}) specifying
#' the points at which tick-marks are drawn at the y-axis.
#' \item{\code{title}}: a character string (default: \code{""}) specifying the
#' text for the title for the plot.
#' \item{\code{subtitle}}: a character string (default: \code{"Two-Sided Confidence Interval"}
#' when \code{adjust = FALSE} or \code{"Two-Sided Difference-Adjusted Confidence Interval"}
#' for the \code{aov.b} function and
#' \code{"Two-Sided Difference-Adjusted Cousineau-Morey Confidence Interval Confidence Interval"}
#' for the \code{aov.w} function when \code{adjust = TRUE}) specifying the text
#' for the subtitle for the plot.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' \item{\strong{Output object from \code{ci.*} Functions}}{The \code{plot}
#' function for the misty object of type \code{"ci.cor"}, \code{"ci.mean"},
#' \code{"ci.median"}, \code{"ci.prop"}, \code{"ci.var"}, and \code{"ci.sd"} has
#' following plotting arguments:
#' \itemize{
#' \item{\code{plot}}: a character string indicating the type of the plot
#' to display, i.e., \code{"ci"} (default) for displaying confidence intervals
#' or \code{"boot"} for displaying bootstrap samples with histograms and density
#' curves when the argument.
#' \item{\code{hist}}: logical: if \code{TRUE} (default), histograms are
#' drawn when \code{plot = "boot"}.
#' \item{\code{density}}: logical: if \code{TRUE} (default), density curves are
#' drawn when \code{plot = "boot"}.
#' \item{\code{point}}: logical: if \code{TRUE} (default), vertical lines
#' representing the point estimate are drawn when \code{plot = "boot"}.
#' \item{\code{ci}}: logical: if \code{TRUE} (default), vertical lines
#' representing the bootstrap confidence intervals are drawn when \code{plot = "boot"}.
#' \item{\code{line}}: logical: if \code{TRUE} (default), a horizontal line
#' is drawn when \code{plot = "ci"} or a vertical line is drawn when
#' \code{plot = "boot"}.
#' \item{\code{point.size}}: a numeric value (default: \code{2.5}) indicating
#' the \code{size} argument in the \code{geom_point} function for controlling
#' the size of points when plotting confidence intervals (\code{plot = "ci"}).
#' \item{\code{point.shape}}: a numeric value between 0 and 25 (default: \code{19})
#' or a character string as plotting symbol indicating the \code{shape} argument
#' in the \code{geom_point} function for controlling the symbols of points
#' when plotting confidence intervals (\code{plot = "ci"}).
#' \item{\code{errorbar.width}}: a numeric value (default: \code{0.3}) indicating
#' the \code{width} argument in the \code{geom_errorbar} function for controlling
#' the width of the whiskers in the \code{geom_errorbar} function when plotting
#' confidence intervals (\code{plot = "ci"}).
#' \item{\code{dodge.width}}: a numeric value (default: \code{0.5}) indicating
#' the \code{width} argument controlling the width of the \code{geom} elements
#' to be dodged when specifying a grouping variable using the argument \code{group}
#' when plotting confidence intervals (\code{plot = "ci"}).
#' \item{\code{binwidth}}: a numeric value or a function (default: \code{NULL})
#' for specifying the \item{\code{bins}}: a numeric value for specifying the
#' \code{bins} argument in the \code{geom_histogram} function for controlling
#' the number of bins when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{hist.alpha}}: a numeric value between 0 and 1 (default: \code{0.4})
#' for specifying the \code{alpha} argument in the \code{geom_histogram}
#' function for controlling the opacity of the bars when plotting bootstrap
#' samples (\code{plot = "boot"}).
#' \item{\code{fill}}: a character string (default: \code{"gray85"}) specifying
#' the \code{fill} argument in the \code{geom_histogram} function controlling
#' the fill aesthetic when plotting bootstrap samples (\code{plot = "boot"}).
#' Note that this argument applied only when no grouping variable was specified
#' \code{group = NULL}.
#' \item{\code{density.col}}: a character string (default: \code{"#0072B2"})
#' specifying the \code{color} argument in the \code{geom_density} function
#' controlling the color of the density curves when plotting bootstrap samples
#' (\code{plot = "boot"}). Note that this argument applied only when no grouping
#' variable was specified \code{group = NULL}.
#' \item{\code{density.linewidth}}: a numeric value (default: \code{0.5}) specifying
#' the \code{linewidth} argument in the \code{geom_density} function controlling
#' the line width of the density curves when plotting bootstrap samples
#' (\code{plot = "boot"}).
#' \item{\code{density.linetype}}: a numeric value or character string (default:
#' \code{0.5}) specifying the \code{linetype} argument in the \code{geom_density}
#' function controlling the line type of the density curves when plotting
#' bootstrap samples (\code{plot = "boot"}).
#' \item{\code{point.col}}: a character string (default: \code{"#CC79A7"}) specifying
#' the \code{color} argument in the \code{geom_vline} function for controlling
#' the color of the vertical line displaying the point estimate when plotting
#' bootstrap samples (\code{plot = "boot"}). Note that this argument applied
#' only when no grouping variable was specified \code{group = NULL}.
#' \item{\code{point.linewidth}}: a numeric value (default: \code{0.6}) specifying
#' the \code{linewdith} argument in the \code{geom_vline} function for
#' controlling the line width of the vertical line displaying the point estimate
#' when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{point.linetype}}: a numeric value or character string (default:
#' \code{"solid"}) specifying the \code{linetype} argument in the \code{geom_vline}
#' function controlling the line type of the vertical line displaying the
#' point estimate when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{ci.col}}: character string (default: \code{"black"}) specifying the
#' \code{color} argument in the \code{geom_vline} function for controlling the
#' color of the vertical line displaying bootstrap confidence intervals when
#' plotting bootstrap samples (\code{plot = "boot"}). Note that this argument
#' applied only when no grouping variable was specified \code{group = NULL}.
#' \item{\code{ci.linewidth}}: a numeric value (default: \code{0.6}) specifying
#' the \code{linewdith} argument in the \code{geom_vline} function for controlling
#' the line width of the vertical line displaying bootstrap confidence intervals
#' when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{ci.linetype}}: a numeric value or character string (default:
#' \code{"dashed"}) specifying the \code{linetype} argument in the \code{geom_vline}
#' function controlling the line type of the vertical line displaying bootstrap
#' confidence intervals when plotting bootstrap samples (\code{plot = "boot"}).
#' \item{\code{intercept}}: a numeric value (default = \code{0}) indicating the
#' \code{yintercept} or \code{xintercept} argument in the \code{geom_hline}
#' or \code{geom_vline} function controlling the position of the horizontal
#' or vertical line when \code{plot = "ci"} and \code{line = TRUE} or when
#' \code{plot = "boot"} and \code{line = TRUE}.
#' \item{\code{linetype}}: a character string (default: \code{"solid"}) indicating
#' the \code{linetype} argument in the \code{geom_hline} or \code{geom_vline}
#' function controlling the line type of the horizontal or vertical line
#' \item{\code{line.col}}: a character string (default: \code{"gray65"}) indicating
#' the \code{color} argument in the \code{geom_hline} or \code{geom_vline}
#' function for controlling the color of the horizontal or vertical line.
#' \item{\code{xlab}}: a character string indicating the \code{name} argument
#' in the \code{scale_x_continuous} function for labeling the x-axis. The default
#' setting is \code{xlab = NULL} when \code{plot = "ci"} and
#' \code{xlab = "Correlation Coefficient"}, \code{xlab = "Arithmetic Mean"},
#' \code{xlab = "Median"}, \code{xlab = "Proportion"}, \code{xlab = "Variance"},
#' or \code{xlab = "Standard Deviation"}.
#' \item{\code{ylab}}: a character string indicating the \code{name} argument
#' in the \code{scale_y_continuous} function for labeling the y-axis. The
#' default setting is \code{ylab = "Correlation Coefficient"}, \code{ylab = "Arithmetic Mean"},
#' \code{ylab = "Median"}, \code{ylab = "Proportion"}, \code{ylab = "Variance"},
#' or \code{ylab = "Standard Deviation"} when \code{plot = "ci"} and
#' \code{ylab = "Probability Density f(x)"} when \code{plot = "boot"}.
#' \item{\code{xlim}}: a numeric vector with two elements indicating the
#' \code{limits} argument in the \code{scale_x_continuous} function for controlling
#' the scale range of the x-axis. The default setting is \code{xlim = NULL}
#' when \code{plot = "ci"} and \code{xlim = c(-1, 1)} for the correlation
#' coefficient and proportion or \code{xlim = NULL) for the arithmetic mean,
#' median, variance and standard deviation when \code{plot = "boot"}.
#' \item{\code{ylim}}: a numeric vector with two elements indicating the
#' \code{limits} argument in the \code{scale_y_continuous} function for controlling
#' the scale range of the y-axis. The default setting is \code{ylim = c(-1, 1)}
#' fpr the correlation coefficient and proportion and \code{ylim = NULL} for
#' the arithmetic mean, median, variance and standard deviation when \code{plot = "ci"}
#' and \code{xlim = NULL} when \code{plot = "boot"}.
#' \item{\code{xbreaks}}: a numeric vector (default: \code{waiver()) indicating
#' the \code{breaks} argument in the \code{scale_x_continuous} function for
#' controlling the x-axis breaks.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()) indicating
#' the \code{breaks} argument in the \code{scale_y_continuous} function for
#' controlling the y-axis breaks.
#' \item{\code{axis.title.size}}: a numeric value (default: \code{11}) indicating
#' the \code{size} argument in the \code{element_text} function for specifying
#' the function controlling the font size of the axis title, i.e.
#' \code{theme(axis.title = element_text(size = axis.text.size))}
#' \item{\code{axis.text.size}}: a numeric value (default: 10) indicating the
#' \code{size} argument in the \code{element_text} function for specifying the
#' function controlling the font size of the axis text,
#' i.e. \code{theme(axis.text = element_text(size = axis.text.size))}.
#' \item{\code{strip.text.size}}: a numeric value (default: \code{11}) indicating
#' the \code{size} argument in the \code{element_text} function for specifying
#' the function controlling the font size of the strip text, i.e.
#' \code{theme(strip.text = element_text(size = strip.text.size))}.
#' \item{\code{title}}: a character string (default: \code{NULL}) indicating the
#' \code{title} argument in the \code{labs} function for the subtitle of the
#' plot.
#' \item{\code{subtitle}}: a character string (default: \code{NULL}) indicating
#' the \code{subtite} argument in the \code{labs} function for the subtitle of
#' the plot.
#' \item{\code{group.col}}: a character vector (default: \code{NULL}) indicating
#' the \code{color} argument in the \code{scale_color_manual} and \code{scale_fill_manual}
#' functions when specifying a grouping variable using the argument \code{group}.
#' \item{\code{plot.margin}}: a numeric vector (default: \code{NA}) with four
#' elements indicating the \code{plot.margin} argument in the \code{theme} function
#' controlling the plot margins. The default setting is \code{c(5.5, 5.5, 5.5, 5.5)}
#' but switches to \code{c(5.5, 5.5, -2.5, 5.5)} when specifying a grouping
#' variable using the argument \code{group}.
#' \item{\code{legend.title}}: a character string (default: \code{""}) indicating
#' the \code{color} argument in the \code{labs} function for specifying the
#' legend title when specifying a grouping variable using the argument \code{group}.
#' \item{\code{legend.position}}: a character string (default: \code{"bottom"})
#' indicating the \code{legend.position} in the \code{theme} argument for
#' controlling the position of the legend function when specifying a
#' grouping variable using the argument \code{group}.
#' \item{\code{legend.box.margin}}: a numeric vector (default: \code{c(-10, 0, 0, 0)})
#' with four elements indicating the \code{legend.box.margin} argument in the
#' \code{theme} function for controlling the margins around the full legend
#' area when specifying a grouping variable using the argument \code{group}.
#' \item{\code{facet.ncol}}: a numeric value (default: \code{NULL}) indicating the
#' \code{ncol} argument in the \code{facet_wrap} function for controlling the
#' number of columns when specifying a split variable using the argument \code{split}.
#' \item{\code{facet.nrow}}: a numeric value (default: \code{NULL}) indicating the
#' \code{nrow} argument in the \code{facet_wrap} function for controlling the
#' number of rows when specifying a split variable using the argument \code{split}.
#' \item{\code{facet.scales}}: a character string (default: \code{"free_y"}) indicating
#' the \code{scales} argument in the \code{facet_wrap} function for controlling the
#' scales shared across facets i.e. \code{"fixed"}, \code{"free_x"},
#' \code{"free_y"} (default) or \code{"free"} when specifying a split variable
#' using the argument \code{split}.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' \item{\strong{Output object from \code{test.levene} Function}}{The \code{plot}
#' function for the misty object of type \code{"test.levene"} has following plotting
#' arguments:
#' \itemize{
#' \item{\code{violin.alpha}}: a numeric value between 0 and 1 (default: \code{0.3})
#' for specifying the \code{alpha} argument in the \code{geom_violin} function
#' for controlling the opacity of the violins.
#' \item{\code{violin.trim}}: logical: if \code{TRUE} (default: \code{FALSE}),
#' the tails of the violins to the range of the data is trimmed.
#' \item{\code{box.alpha}}: a numeric value between 0 and 1 (default: \code{0.2})
#' for specifying the \code{alpha} argument in the \code{geom_boxplot} function
#' for controlling the opacity of the boxplots.
#' \item{\code{box.width}}: a numeric value between 0 and 1 (default: \code{0.2})
#' for specifying the \code{alpha} argument in the \code{geom_boxplot} function
#' for controlling the opacity of the boxplots.
#' \item{\code{jitter.size}}: a numeric value (default: \code{1.25}) indicating
#' the \code{size} aesthetic for the jittered data points.
#' \item{\code{jitter.width}}: a numeric value (default: \code{0.05}) indicating
#' the amount of horizontal jitter.
#' \item{\code{jitter.height}}: a numeric value (default: \code{0}) indicating
#' the amount of vertical jitter.
#' \item{\code{jitter.alpha}}: a numeric value between 0 and 1 (default: \code{0.2})
#' for specifying the \code{alpha} argument in the \code{geom_jitter} function
#' for controlling the opacity of the jittered data points.
#' \item{\code{start}}: a numeric value between 0 and 1 (default: \code{0.9}),
#' graphical parameter to specify the gray value at the low end of the palette.
#' \item{\code{end}}: a numeric value between 0 and 1 (default: \code{0.4}),
#' graphical parameter to specify the gray value at the high end of the palette.
#' \item{\code{color}}: a character vector (default: \code{NULL}), indicating
#' the color of the violins and the boxes. By default, default ggplot2 colors
#' are used.
#' \item{\code{xlab}}: a character string (default: \code{NULL}) specifying
#' the labels for the x-axis.
#' \item{\code{ylab}}: a character string (default: \code{NULL}) specifying
#' the labels for the y-axis.
#' \item{\code{ylim}}: a numeric vector (default: \code{NULL}) of length two specifying
#' limits of the limits of the y-axis.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()})
#' specifying the points at which tick-marks are drawn at the y-axis.
#' \item{\code{title}}: a character string (default: \code{""}) specifying the
#' text for the title for the plot.
#' \item{\code{subtitle}}: a character string (default: \code{""}) specifying
#' the text for the subtitle for the plot.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' \item{\strong{Output object from \code{test.t} and \code{test.z}}}{The \code{plot}
#' function for the misty object of type \code{"test.t"} and \code{"test.z"} has
#' following plotting arguments:
#' \itemize{
#' \item{\code{bar}}: logical: if \code{TRUE} (default), bars representing means
#' for each groups are drawn.
#' \item{\code{point}}: logical: if \code{TRUE}, points representing means for
#' each groups are drawn.
#' \item{\code{ci}}: logical: if \code{TRUE} (default), error bars representing
#' confidence intervals are drawn.
#' \item{\code{jitter}}: logical: if \code{TRUE}, jittered data points are drawn.
#' \item{\code{line}}: logical: if \code{TRUE} (default), a horizontal line is
#' drawn at \code{mu} for the one-sample t- or z-test or at 0 for the paired-sample
#' t- or z-test.
#' \item{\code{conf.level}}: a numeric value between 0 and 1 (default: 0.95)
#' indicating the confidence level of the interval.
#' \item{\code{adjust}}: logical: if \code{TRUE} (default), difference-adjustment
#' for the confidence intervals in a two-sample design is applied.
#' \item{\code{point.size}}: a numeric value indicating the \code{size} (default:
#' \code{3}) aesthetic for the point representing the mean value.
#' \item{\code{errorbar.width}}: a numeric value (default: \code{0.1}) indicating
#' the horizontal bar width of the error bar.
#' \item{\code{linetype}}: an integer value or character string (default: \code{3})
#' specifying the line type for the line representing the population mean under
#' the null hypothesis, i.e., 0 = blank, 1 = solid, 2 = dashed, 3 = dotted,
#' 4 = dotdash, 5 = longdash, or 6 = twodash.
#' \item{\code{linewidth}}: a numeric value indicating the \code{linewidth}
#' (default: \code{0.8} aesthetic for the line representing the population mean
#' under the null hypothesis.
#' \item{\code{jitter.size}}: a numeric value (default: \code{1.25}) indicating
#' the \code{size} aesthetic for the jittered data points.
#' \item{\code{jitter.width}}: a numeric value (default: \code{0.05}) indicating
#' the amount of horizontal jitter.
#' \item{\code{jitter.height}}: a numeric value (default: \code{0}) indicating
#' the amount of vertical jitter.
#' \item{\code{jitter.alpha}}: a numeric value between 0 and 1 (default: \code{0.1})
#' for specifying the \code{alpha} argument in the \code{geom_jitter} function
#' for controlling the opacity of the jittered data points.
#' \item{\code{xlab}}: a character string (default: \code{NULL}) specifying the
#' labels for the x-axis.
#' \item{\code{ylab}}: a character string (default: \code{"y"}) specifying the
#' labels for the y-axis.
#' \item{\code{ylim}}: a numeric vector of length two (default: \code{NULL})
#' specifying limits of the limits of the y-axis.
#' \item{\code{ybreaks}}: a numeric vector (default: \code{waiver()}) specifying
#' the points at which tick-marks are drawn at the y-axis.
#' \item{\code{title}}: a character string (default: \code{""}) specifying the
#' text for the title for the plot.
#' \item{\code{subtitle}}: a character string (default: \code{"Two-Sided Confidence Interval"}
#' when \code{adjust = FALSE} or \code{"Two-Sided Difference-Adjusted Confidence Interval"}
#' when \code{adjust = TRUE}) specifying the text for the subtitle for the plot.
#' \item{\code{filename}}: character string indicating the \code{filename}
#' argument including the file extension in the \code{ggsave} function.
#' \item{\code{width}}: a numeric value indicating the \code{width} argument
#' for the \code{ggsave} function.
#' \item{\code{height}}: a numeric value indicating the \code{height} argument
#' for the \code{ggsave} function.
#' \item{\code{dpi}}: a numeric value indicating the \code{dpi} argument for
#' the \code{ggsave} function.
#' \item{\code{units}}: a character string (default: \code{"in"}) indicating
#' the \code{units} argument (default: \code{in}) for the \code{ggsave}
#' function.
#' }
#' }
#' }
#'
#' @author
#' Takuya Yanagida \email{takuya.yanagida@@univie.ac.at}
#'
#' @method plot misty.object
#'
#' @export
plot.misty.object <- function(x, plot = x$args$plot, bar = x$args$bar,
box = x$args$box, violin = x$args$violin,
hist = x$args$hist,point = x$args$point,
line = x$args$line, ci = x$args$ci,
conf.level = x$args$conf.level, adjust = x$args$adjust,
jitter = x$args$jitter, density = x$args$density,
square = x$args$square, rotate = x$args$rotate,
binwidth = x$args$binwidth, bins = x$args$bins,
fill = x$args$fill, hist.alpha = x$args$hist.alpha,
tile.alpha = x$args$tile.alpha, violin.alpha = x$args$violin.alpha,
violin.trim = x$args$violin.trim, box.width = x$args$box.width,
box.alpha = x$args$box.alpha, linetype = x$args$linetype,
linewidth = x$args$linewidth, line.col = x$args$line.col,
intercept = x$args$intercept, density.col = x$args$density.col,
density.linewidth = x$args$density.linewidth,
density.linetype = x$args$density.linetype,
point.size = x$args$point.size,
point.linewidth = x$args$point.linewidth,
point.linetype = x$args$point.linetype,
point.shape = x$args$point.shape,
point.col = x$args$point.col, ci.col = x$args$ci.col,
ci.linewidth = x$args$ci.linewidth, ci.linetype = x$args$ci.linetype,
errorbar.width = x$args$errorbar.width, dodge.width = x$args$dodge.width,
jitter.size = x$args$jitter.size, jitter.width = x$args$jitter.width,
jitter.height = x$args$jitter.height, jitter.alpha = x$args$jitter.alpha,
gray = x$args$gray, start = x$args$start, end = x$args$end,
color = x$args$color, xlab = x$args$xlab, ylab = x$args$ylab,
xlim = x$args$xlim, ylim = x$args$ylim, xbreaks = x$args$xbreaks,
ybreaks = x$args$ybreaks, axis.title.size = x$args$axis.title.sizes,
axis.text.size = x$args$axis.text.size, strip.text.size = x$args$strip.text.size,
title = x$args$title, subtitle = x$args$subtitle,
group.col = x$args$group.col, plot.margin = x$args$plot.margin,
legend.title = x$args$legend.title, legend.position = x$args$legend.position,
legend.box.margin = x$args$legend.box.margin, legend.key.size = x$args$legend.key.size,
legend.text.size = x$args$legend.text.size, facet.ncol = x$args$facet.ncol,
facet.nrow = x$args$facet.nrow, facet.scales = x$args$facet.scales,
filename = x$args$filename, width = x$args$width, height = x$args$height,
units = x$args$units, dpi = x$args$dpi, check = TRUE, ...) {
#_____________________________________________________________________________
#
# Initial Check --------------------------------------------------------------
# Check if input 'x' is missing or NULL
if (isTRUE(missing(x) || is.null(x))) { stop("Please specify a misty object for the argument 'x'.", call. = FALSE) }
# Check if input 'x' is a misty object
if (isTRUE(!inherits(x, what = "misty.object"))) { stop("Please specify a misty object for the argument 'x'.", call. = FALSE) }
# Check if input 'x' is supported by the function
if (isTRUE(!x$type %in% c("aov.b", "aov.w", "boot.bs", "ci.cor", "ci.mean", "ci.median", "ci.prop", "ci.var", "ci.sd", "item.dfi", "multilevel.r2", "multilevel.r2.manual", "na.pattern", "test.levene", "test.welch", "test.z", "test.t"))) { stop("This type of misty object is not supported by the plot.misty.object() function.", call. = FALSE) }
#_____________________________________________________________________________
#
# Input Check-----------------------------------------------------------------
# Global Variables
group <- id <- low <- m <- m.diff <- m.low <- m.upp <- mu <- n.pattern <- obs_miss <- part <- pattern <- upp <- variable <- NULL
#_____________________________________________________________________________
#
# Between-Subject Analysis of Variance (ANOVA) -------------------------------
switch(x$type, "aov.b" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Means and (Difference-Adjusted) Confidence Intervals by Group ####
ci.table <- misty::ci.mean(x$data, y, group = "group", adjust = adjust, conf.level = conf.level, output = FALSE)$result
#—————————————————————————————————————— # #
### Create ggplot ####
# Subtitle
if (isTRUE(ci)) { if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Interval") } else { subtitle } } else { subtitle <- "" }
p <- ggplot2::ggplot(x$data, ggplot2::aes(group, y)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#—————————————————————————————————————— # #
### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = ci.table, ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#—————————————————————————————————————— # #
### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = ci.table, ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#—————————————————————————————————————— # #
### Points ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = ci.table, ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#—————————————————————————————————————— # #
### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#_____________________________________________________________________________
#
# Repeated Measures Analysis of Variance (Within-Subject ANOVA ---------------
}, "aov.w" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(linewidth)) { linewidth <- 0.5 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Compute Means and (Difference-Adjusted) Confidence Intervals by Group ####
ci.table <- misty::ci.mean.w(x$data$wide, adjust = adjust, conf.level = conf.level, na.omit = x$args$na.omit, check = FALSE, output = FALSE)$result
#—————————————————————————————————————— # #
### Create ggplot ####
# Subtitle
if (isTRUE(ci)) { if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Cousineau-Morey Confidence Interval") } else { subtitle } } else { subtitle <- "" }
p <- ggplot2::ggplot(x$data$long, ggplot2::aes(time, y, group = 1L)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#—————————————————————————————————————— # #
### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = ci.table, ggplot2::aes(variable, m, ymin = low, ymax = upp), width = errorbar.width)) }
#—————————————————————————————————————— # #
### Points ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = ci.table, ggplot2::aes(variable, m), stat = "identity", size = point.size)) }
#—————————————————————————————————————— # #
### Lines ####
if (isTRUE(line)) { p <- p + suppressWarnings(ggplot2::geom_line(data = ci.table, ggplot2::aes(variable, m), stat = "identity", linewidth = linewidth)) }
#—————————————————————————————————————— # #
### Add jittered points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#—————————————————————————————————————— # #
### Individual lines ####
if (isTRUE(jitter && line)) { p <- p + ggplot2::geom_line(data = x$data$long, ggplot2::aes(time, y, group = id), alpha = jitter.alpha, position = ggplot2::position_dodge(jitter.width)) }
#_____________________________________________________________________________
#
# Bollen-Stine Bootstrap with Incomplete Data, boot.bs() ---------------------
}, "boot.bs" = {
chisq <- NULL
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Data ####
plotdat <- data.frame(chisq = x$boot.chisq)
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create ggplot ####
p <- ggplot2::ggplot(plotdat, ggplot2::aes(chisq)) +
ggplot2::theme_bw() +
ggplot2::geom_histogram(ggplot2::aes(y = ggplot2::after_stat(density)), color = "black", alpha = 0.4, fill = "gray85") +
ggplot2::geom_density(color = "#0072B2") +
ggplot2::geom_vline(ggplot2::aes(xintercept = x$result$chisq, color = "Observed Test Statistic")) +
ggplot2::scale_x_continuous(name = expression(paste(chi^2, " Test Statistic")), limits = c(0L, max(c(plotdat$chisq, x$result$chisq), na.rm = TRUE))) +
ggplot2::scale_y_continuous(name = "Probability Density, f(x)", expand = ggplot2::expansion(mult = c(0L, 0.05))) +
ggplot2::scale_color_manual(values = c("Observed Test Statistic" = "#CC79A7")) +
ggplot2::theme(legend.position = "bottom",
legend.box.margin = ggplot2::margin(-15L, 0L, 0L, 0L),
legend.title = ggplot2::element_blank(),
legend.background = ggplot2::element_rect(fill = "transparent"))
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Correlation Coefficients --------------
}, "ci.cor" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab', 'ylab', 'xlim' and 'ylim' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Correlation Coefficient" } else { ylab }
ylim <- if (isTRUE(is.null(ylim))) { c(-1, 1) } else { ylim }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Correlation Coefficient" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
xlim <- if (isTRUE(is.null(xlim))) { c(-1, 1) } else { xlim }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Correlation Coefficient with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "cor", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
stop("There are no confidence intervals for the correlation coefficient to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (isTRUE(any(!is.na(x$boot$cor)))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "cor", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
stop("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Arithmetic Means ----------------------
}, "ci.mean" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Arithmetic Mean" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Arithmetic Mean" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Arithmetic Mean with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "m", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
plot <- "none"
warning("There are no confidence intervals for the arithmetic mean to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$m))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "m", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
plot <- "none"
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Median --------------------------------
}, "ci.median" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Arithmetic Mean" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Arithmetic Mean" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Median with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "med", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the median to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$med))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "med", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Proportions ---------------------------
}, "ci.prop" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab', 'ylab', and 'ylim' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Proportion" } else { ylab }
ylim <- if (isTRUE(is.null(ylim))) { c(0, 1) } else { ylim }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Proportion" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
xlim <- if (isTRUE(is.null(xlim))) { c(0, 1) } else { xlim }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Proportion with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "prop", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the proportion to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$prop))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "prop", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Variances -----------------------------
}, "ci.var" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Variance" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Variance" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Variance with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "var", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the variance to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$var))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "var", group = x$data$group, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# (Bootstrap) Confidence Intervals for Standard Deviations -------------------
}, "ci.sd" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (isTRUE(is.null(plot))) { plot <- "ci" }
if (isTRUE(is.null(point.size))) { point.size <- 2.5 }
if (isTRUE(is.null(point.shape))) { point.shape <- 19 }
if (isTRUE(is.null(errorbar.width))) { errorbar.width <- 0.3 }
if (isTRUE(is.null(dodge.width))) { dodge.width <- 0.5 }
if (isTRUE(is.null(hist.alpha))) { hist.alpha <- 0.4 }
if (isTRUE(is.null(fill))) { fill <- "gray85" }
if (isTRUE(is.null(density.col))) { density.col <- "#0072B2" }
if (isTRUE(is.null(density.linewidth))) { density.linewidth <- 0.5 }
if (isTRUE(is.null(density.linetype))) { density.linetype <- "solid" }
if (isTRUE(is.null(point.col))) { point.col <- "#CC79A7" }
if (isTRUE(is.null(point.linewidth))) { point.linewidth <- 0.6 }
if (isTRUE(is.null(point.linetype))) { point.linetype <- "solid" }
if (isTRUE(is.null(ci.col))) { ci.col <- "black" }
if (isTRUE(is.null(ci.linewidth))) { ci.linewidth <- 0.6 }
if (isTRUE(is.null(ci.linetype))) { ci.linetype <- "dashed" }
if (isTRUE(is.null(intercept))) { intercept <- 0L }
if (isTRUE(is.null(linetype))) { linetype <- "solid" }
if (isTRUE(is.null(line.col))) { line.col <- "gray65" }
if (isTRUE(is.null(xbreaks))) { xbreaks <- ggplot2::waiver() }
if (isTRUE(is.null(ybreaks))) { ybreaks <- ggplot2::waiver() }
if (isTRUE(is.null(axis.title.size))) { axis.title.size <- 11L }
if (isTRUE(is.null(axis.text.size))) { axis.text.size <- 10L }
if (isTRUE(is.null(strip.text.size))) { strip.text.size <- 11L }
if (isTRUE(is.null(legend.title))) { legend.title <- "" }
if (isTRUE(is.null(legend.position))) { legend.position <- "bottom" }
if (isTRUE(is.null(legend.box.margin))) { legend.box.margin <- c(-10L, 0L, 0L, 0L) }
if (isTRUE(is.null(facet.scales))) { facet.scales <- "free_y" }
if (is.null(units)) { units <- "in" }
#—————————————————————————————————————— #
### 'xlab' and 'ylab' Argument ####
switch(plot, "ci" = {
ylab <- if (isTRUE(is.null(ylab))) { "Variance" } else { ylab }
}, "boot" = {
xlab <- if (isTRUE(is.null(xlab))) { "Variance" } else { xlab }
ylab <- if (isTRUE(is.null(ylab))) { "Probability Density, f(x)" } else { ylab }
})
#—————————————————————————————————————— #
### 'plot.margin' Argument ####
if (isTRUE(is.null(plot.margin))) { if (isTRUE(is.null(x$data$group))) { plot.margin <- c(5.5, 5.5, 5.5, 5.5) } else { plot.margin <- c(5.5, 5.5, -2.5, 5.5) } }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Standard Deviation with Error Bars ####
switch(plot, "ci" = {
if (isTRUE(any(!is.na((if (isTRUE(!is.data.frame(x$result))) { do.call("rbind", x$result) } else { x$result })$low)))) {
p <- .plot.ci(result = x$result, stat = "sd", group = x$data$group, split = x$data$split, point.size = point.size, point.shape = point.shape, errorbar.width = errorbar.width, dodge.width = dodge.width, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no confidence intervals for the standard deviation to plot.", call. = FALSE)
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Bootstrap Samples ####
}, "boot" = {
if (any(!is.na(x$boot$sd))) {
p <- .plot.boot(result = x$result, boot.sample = x$boot, stat = "sd", group = x$datagroup, split = x$data$split, hist = hist, binwidth = binwidth, bins = bins, alpha = hist.alpha, fill = fill, density = density, density.col = density.col, density.linewidth = density.linewidth, density.linetype = density.linetype, plot.point = point, point.col = point.col, point.linewidth = point.linewidth, point.linetype = point.linetype, plot.ci = ci, ci.col = ci.col, ci.linewidth = ci.linewidth, ci.linetype = ci.linetype, line = line, intercept = intercept, linetype = linetype, line.col = line.col, xlab = xlab, ylab = ylab, xlim = xlim, ylim = ylim, xbreaks = xbreaks, ybreaks = ybreaks, axis.title.size = axis.title.size, axis.text.size = axis.text.size, strip.text.size = strip.text.size, title = title, subtitle = subtitle, group.col = group.col, plot.margin = plot.margin, legend.title = legend.title, legend.position = legend.position, legend.box.margin = legend.box.margin, facet.ncol = facet.ncol, facet.nrow = facet.nrow, facet.scales = facet.scales)$p
} else {
warning("There are no bootstrap samples to plot.", call. = FALSE)
}
})
#_____________________________________________________________________________
#
# Dynamic Fit Index Cutoffs --------------------------------------------------
}, "item.dfi" = {
fit <- cutoff <- NULL
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Data ####
#—————————————————————————————————————— #
### Level 0 ####
if (isTRUE(length(x$result$fit.sim) == 1L)) {
df <- data.frame(level = "Level 0", group = "True",
index = factor(rep(c("CFI", "TLI", "RMSEA", "SRMR"), each = x$args$nrep), levels = c("CFI", "TLI", "RMSEA", "SRMR")),
fit = unlist(x$result$fit.sim[["Level 0"]]),
cutoff = rep( unlist(x$result$fit.cutoff["Level 0", c("cfi", "tli", "rmsea", "srmr")]), each = x$args$nrep))
#—————————————————————————————————————— #
### Level 0, 1, 2, and/or 3 ####
} else {
df <- NULL
for (i in setdiff(names(x$result$fit.sim), "Level 0")) {
df <- rbind(df,
data.frame(level = i,
rbind(data.frame(group = "True",
index = factor(rep(c("CFI", "TLI", "RMSEA", "SRMR"), each = x$args$nrep), levels = c("CFI", "TLI", "RMSEA", "SRMR")),
fit = unlist(x$result$fit.sim[["Level 0"]]),
cutoff = rep( unlist(x$result$fit.cutoff["Level 0", c("cfi", "tli", "rmsea", "srmr")]), each = x$args$nrep)),
data.frame(group = "Misspecified",
index = factor(rep(c("CFI", "TLI", "RMSEA", "SRMR"), each = x$args$nrep), levels = c("CFI", "TLI", "RMSEA", "SRMR")),
fit = unlist(x$result$fit.sim[[i]]),
cutoff = rep( unlist(x$result$fit.cutoff[i, c("cfi", "tli", "rmsea", "srmr")]), each = x$args$nrep)))))
}
df$group <- factor(df$group, levels = c("True", "Misspecified"))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot ####
p <- ggplot2::ggplot(df, ggplot2::aes(fit, group = group, color = group, fill = group)) +
ggplot2::theme_bw() +
ggplot2::geom_histogram(position = "identity", color = "gray60", alpha = 0.5) +
ggplot2::geom_vline(ggplot2::aes(xintercept = cutoff, group = group, color = group), linetype = "longdash") +
ggplot2::scale_fill_manual(values = c("#56B4E9", "#E9798C"))+
ggplot2::scale_color_manual(values = c("#56B4E9", "#E9798C"))+
ggplot2::facet_grid(level ~ index, scales = "free_x" ) +
ggplot2::scale_x_continuous(name = "") +
ggplot2::scale_y_continuous(name = "Count", expand = ggplot2::expansion(mult = c(0L, 0.05))) +
ggplot2::theme(legend.position = "bottom",
legend.box.margin = ggplot2::margin(-20L, 0L, 0L, 0L),
legend.title = ggplot2::element_blank(),
legend.background = ggplot2::element_rect(fill = "transparent"),
strip.text = ggplot2::element_text(size = 11))
#_____________________________________________________________________________
#
# R-Squared Measures for Multilevel and LMMs ---------------------------------
}, "multilevel.r2" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Not Cluster-Mean-Centered ####
# Predictors are not cluster-mean-centered
if (isTRUE(ncol(x$result$rs$decomp) == 1L)) {
df <- data.frame(var = factor(rep("Total", times = 4L)),
part = factor(c("Fixed Slopes", "Slope Variation", "Intercept Variation", "Residual"), levels = c("Residual", "Intercept Variation", "Slope Variation", "Fixed Slopes")),
y = as.vector(x$result$rs$decomp))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Cluster-Mean-Centered ####
} else {
df <- data.frame(var = factor(rep(c("Total", "Within", "Between"), each = 5L), levels = c("Total", "Within", "Between")),
part = factor(c("Fixed Slopes (Within)", "Fixed Slopes (Between)","Slope Variation (Within)", "Intercept Variation (Between)", "Residual (Within)"), levels = c("Residual (Within)", "Intercept Variation (Between)", "Slope Variation (Within)", "Fixed Slopes (Between)", "Fixed Slopes (Within)")),
y = as.vector(x$result$rs$decomp))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot ####
p <- ggplot2::ggplot(df, ggplot2::aes(x = var, y = y, fill = part)) +
ggplot2::geom_bar(stat = "identity") +
ggplot2::scale_y_continuous(name = "Proportion of Variance", breaks = seq(0L, 1L, by = 0.1)) +
ggplot2::theme_bw() +
ggplot2::theme(axis.title.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
legend.box.margin = ggplot2::margin(-10L, 6L, 6L, 6L)) +
ggplot2::guides(fill = ggplot2::guide_legend(nrow = 2L, reverse = TRUE))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Gray Color Scales ####
if (isTRUE(gray)) {
p <- p + ggplot2::scale_fill_grey(start = end, end = start)
} else {
p <- p + ggplot2::scale_fill_manual(values = rev(color))
}
#_____________________________________________________________________________
#
# R-Squared Measures for Multilevel and LMMS, Manual Input -------------------
}, "multilevel.r2.manual" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Not Cluster-Mean-Centered ####
# Predictors are not cluster-mean-centered
if (isTRUE(ncol(x$result$decomp) == 1L)) {
df <- data.frame(var = factor(rep("Total", times = 4L)),
part = factor(c("Fixed Slopes", "Slope Variation", "Intercept Variation", "Residual"), levels = c("Residual", "Intercept Variation", "Slope Variation", "Fixed Slopes")),
y = as.vector(x$result$decomp))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Predictors Cluster-Mean-Centered ####
} else {
df <- data.frame(var = factor(rep(c("Total", "Within", "Between"), each = 5L), levels = c("Total", "Within", "Between")),
part = factor(c("Fixed Slopes (Within)", "Fixed Slopes (Between)","Slope Variation (Within)", "Intercept Variation (Between)", "Residual (Within)"), levels = c("Residual (Within)", "Intercept Variation (Between)", "Slope Variation (Within)", "Fixed Slopes (Between)", "Fixed Slopes (Within)")),
y = as.vector(x$result$decomp))
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot ####
p <- ggplot2::ggplot(df, ggplot2::aes(x = var, y = y, fill = part)) +
ggplot2::geom_bar(stat = "identity") +
ggplot2::scale_y_continuous(name = "Proportion of Variance", breaks = seq(0L, 1L, by = 0.1)) +
ggplot2::theme_bw() +
ggplot2::theme(axis.title.x = ggplot2::element_blank(),
axis.ticks.x = ggplot2::element_blank(),
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
legend.box.margin = ggplot2::margin(-10L, 6L, 6L, 6L)) +
ggplot2::guides(fill = ggplot2::guide_legend(nrow = 2L, reverse = TRUE))
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Gray Color Scales ####
if (isTRUE(gray)) {
p <- p + ggplot2::scale_fill_grey(start = end, end = start)
} else {
p <- p + ggplot2::scale_fill_manual(values = rev(color))
}
#_____________________________________________________________________________
#
# Missing Data Pattern ------------------------------------------------------
}, "na.pattern" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Plot Data ####
plotdat <- do.call("rbind", apply(x$result[-nrow(x$result), c("pattern", colnames(x$data))], 1, function(y) {
data.frame(pattern = y["pattern"], var = colnames(x$data), obs_miss = y[colnames(x$data)], x = seq_len(ncol(x$data)), row.names = NULL)
}))
# Factor
plotdat$obs_miss <- factor(ifelse(plotdat$obs_miss == 1L, "Observed", "Missing"))
# Patterns excluded
if (isTRUE(!is.null(x$args$n.pattern))) {
n.pattern.exclude <- names(which(table(apply(is.na(x$data), 1L, function(y) paste(as.numeric(y), collapse = ""))) < x$args$n.pattern))
} else {
n.pattern.exclude <- NULL
}
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create ggplot ####
p <- ggplot2::ggplot(plotdat, ggplot2::aes(x, pattern, fill = obs_miss, alpha = tile.alpha)) +
ggplot2::geom_tile(color = "black") +
ggplot2::scale_fill_manual(values = c("Missing" = color[1L], "Observed" = color[2L])) +
ggplot2::scale_alpha_continuous(limits = c(0, 1), guide = "none") +
ggplot2::scale_x_continuous("Number of Missing Entries per Variable",
breaks = seq_len(length(colnames(x$data))),
labels = as.character(x$result[nrow(x$result), colnames(x$data)]),
sec.axis = ggplot2::dup_axis(labels = colnames(x$data), name = "Variable")) +
ggplot2::scale_y_reverse("Pattern Frequency",
breaks = seq_len(length(x$result$n) - 1L), labels = x$result[-nrow(x$result), "n"],
sec.axis = ggplot2::dup_axis(labels = x$result[-nrow(x$result), "nNA"], name = "Number of Missing Entries per Pattern")) +
ggplot2::theme(plot.margin = ggplot2::margin(t = plot.margin[1L], r = plot.margin[2L], b = plot.margin[3L], l = plot.margin[4L]),
legend.title = ggplot2::element_blank(),
legend.position = "bottom",
legend.key.size = ggplot2::unit(legend.key.size, "pt"),
legend.text = ggplot2::element_text(size = legend.text.size),
legend.box.margin = ggplot2::margin(t = legend.box.margin[1L], r = legend.box.margin[2L], b = legend.box.margin[3L], l = legend.box.margin[4L]),
panel.grid.minor = ggplot2::element_blank(), panel.grid.major = ggplot2::element_blank())
### Square Plot Tiles ####
if (isTRUE(square)) { p <- p + ggplot2::coord_fixed(expand = FALSE) } else { p <- p + ggplot2::coord_cartesian(expand = FALSE) }
### Rotate Labels ####
if (isTRUE(rotate)) { p <- p + ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 90L)) }
### Caption ####
if (isTRUE(length(n.pattern.exclude) != 0L)) {
p <- p + ggplot2::labs(caption = paste0("Note. ", length(n.pattern.exclude), ifelse(length(n.pattern.exclude) == 1L, " pattern ", " patterns "), " with less than ", n.pattern, " cases removed.")) +
ggplot2::theme(plot.caption = ggplot2::element_text(hjust = 0.5, vjust = 5))
}
#_____________________________________________________________________________
#
# Levene's Test for Homogeneity of Variance ----------------------------------
}, "test.levene" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(violin.alpha)) { violin.alpha <- 0.3 }
if (is.null(violin.trim)) { violin.trim <- FALSE }
if (is.null(box.alpha)) { box.alpha <- 0.2 }
if (is.null(box.width)) { box.width <- 0.2 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(gray)) { gray <- FALSE }
if (is.null(start)) { start <- 0.9 }
if (is.null(end)) { end <- 0.4 }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create Plot ####
p <- ggplot2::ggplot(x$data, ggplot2::aes(group, y, fill = group)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5),
plot.title = ggplot2::element_text(hjust = 0.5)) +
ggplot2::guides(fill = "none")
# Add violin plots
if (isTRUE(violin)) { p <- p + ggplot2::geom_violin(alpha = violin.alpha, trim = violin.trim) }
# Add boxplots
if (isTRUE(box)) { p <- p + ggplot2::geom_boxplot(alpha = box.alpha, width = box.width) }
# Add jittered points
if (isTRUE(jitter)) { p <- p + ggplot2::geom_jitter(alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size) }
# Gray color scales
if (isTRUE(gray)) {
p <- p + ggplot2::scale_fill_grey(start = start, end = end)
# User-specified colors
} else {
if (isTRUE(!is.null(color))) { p <- p + ggplot2::scale_fill_manual(values = color) }
}
#_____________________________________________________________________________
#
# t-Test ---------------------------------------------------------------------
}, "test.t" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(linetype)) { linetype <- 3 }
if (is.null(linewidth)) { linewidth <- 0.8 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## One-, Two-, or Paired Sample ####
switch(x$sample,
#—————————————————————————————————————— #
### One-Sample ####
"one" = {
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0, m), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0, m, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(data = data.frame(mu = x$args$mu), ggplot2::aes(yintercept = mu), linetype = linetype, linewidth = linewidth) }
#—————————————————————————————————————— #
### Two-Sample ####
}, "two" = {
# Plot data
plotdat <- split(x$data[, 1L], f = x$data[, 2L]) |> (\(y) data.frame(group = factor(c(rep(x$result[1L, "group"], times = length(y[[1L]])), rep(x$result[2L, "group"], times = length(y[[2L]])))), y = unlist(y)) )()
# Confidence interval
ci.table <- misty::ci.mean(plotdat[, "y"], group = plotdat[, "group"], adjust = adjust, conf.level = conf.level, output = FALSE)$result
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Interval") } else { subtitle }
p <- ggplot2::ggplot(ci.table, ggplot2::aes(group, m)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) + ggplot2::theme_bw() +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = plotdat, ggplot2::aes(x = group, y = y), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#—————————————————————————————————————— #
### Paired-Sample ####
}, "paired" = {
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0, m.diff), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0, m.diff), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0, m.diff, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(yintercept = 0L, linetype = linetype, linewidth = linewidth) }
})
#_____________________________________________________________________________
#
# Welch's Test ---------------------------------------------------------------
}, test.welch = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.2 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Means and (Difference-Adjusted) Confidence Intervals by Group ####
ci.table <- x$result$descript
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Create ggplot ####
# Subtitle
if (isTRUE(ci)) { if (isTRUE(subtitle == "Confidence Intervals")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Intervals") } else { subtitle } } else { subtitle <- "" }
p <- ggplot2::ggplot(x$data, ggplot2::aes(group, y)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::theme_bw() +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#—————————————————————————————————————— #
### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = ci.table, ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#—————————————————————————————————————— #
### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = ci.table, ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#—————————————————————————————————————— #
### Points ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = ci.table, ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#—————————————————————————————————————— #
### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = x$data, ggplot2::aes(group, y), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#_____________________________________________________________________________
#
# z-Test ---------------------------------------------------------------------
}, "test.z" = {
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## Default Argument Specification ####
if (is.null(point.size)) { point.size <- 3 }
if (is.null(errorbar.width)) { errorbar.width <- 0.1 }
if (is.null(linetype)) { linetype <- 3 }
if (is.null(linewidth)) { linewidth <- 0.8 }
if (is.null(jitter.size)) { jitter.size <- 1.25 }
if (is.null(jitter.width)) { jitter.width <- 0.05 }
if (is.null(jitter.height)) { jitter.height <- 0 }
if (is.null(jitter.alpha)) { jitter.alpha <- 0.1 }
if (is.null(subtitle)) { subtitle <- "Confidence Interval" }
if (is.null(ylab)) { ylab <- "y" }
if (is.null(ybreaks)) { ybreaks <- ggplot2::waiver() }
if (is.null(units)) { units <- "in" }
#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
## One-, Two-, or Paired Sample ####
switch(x$sample,
#—————————————————————————————————————— #
### One-Sample ####
"one" = {
#···················
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#···················
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0L, m), stat = "summary", fun = "mean")) }
#···················
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0L, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0L, m, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(data = data.frame(mu = x$args$mu), ggplot2::aes(yintercept = mu), linetype = linetype, linewidth = linewidth) }
#—————————————————————————————————————— #
### Two-Sample ####
}, "two" = {
# Plot data
plotdat <- split(x$data[, 1L], f = x$data[, 2L]) |> (\(y) data.frame(group = factor(c(rep(x$result[1L, "group"], times = length(y[[1L]])), rep(x$result[2L, "group"], times = length(y[[2L]])))), y = unlist(y)))()
# Confidence interval
ci.table <- misty::ci.mean(plotdat[, "y"], group = plotdat[, "group"], adjust = adjust, conf.level = conf.level, output = FALSE)$result
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% ", ifelse(isTRUE(adjust), "Difference-Adjusted ", ""), "Confidence Interval") } else { subtitle }
p <- ggplot2::ggplot(ci.table, ggplot2::aes(group, m)) +
ggplot2::scale_x_discrete(name = xlab) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) + ggplot2::theme_bw() +
ggplot2::theme(plot.subtitle = ggplot2::element_text(hjust = 0.5), plot.title = ggplot2::element_text(hjust = 0.5))
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(ggplot2::aes(group, m), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(ggplot2::aes(group, m), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(ggplot2::aes(group, m, ymin = low, ymax = upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = plotdat, ggplot2::aes(x = group, y = y), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#—————————————————————————————————————— #
### Paired-Sample ####
}, "paired" = {
#...................
#### Create ggplot ####
# Subtitle
if (isTRUE(subtitle == "Confidence Interval")) { subtitle <- paste0("Two-Sided ", round(conf.level * 100L, digits = 2L), "% Confidence Interval") }
p <- ggplot2::ggplot(data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x)) +
ggplot2::scale_x_continuous(name = xlab, limits = c(-2L, 2L)) +
ggplot2::scale_y_continuous(name = ylab, limits = ylim, breaks = ybreaks) +
ggplot2::labs(title = title, subtitle = subtitle) +
ggplot2::theme_bw() + ggplot2::theme(plot.title = ggplot2::element_text(hjust = 0.5),
plot.subtitle = ggplot2::element_text(hjust = 0.5),
axis.text.x = ggplot2::element_blank(), axis.ticks.x = ggplot2::element_blank())
#...................
#### Bars ####
if (isTRUE(bar)) { p <- p + suppressWarnings(ggplot2::geom_bar(data = x$result, ggplot2::aes(0L, m.diff), stat = "summary", fun = "mean")) }
#...................
#### Point ####
if (isTRUE(point)) { p <- p + suppressWarnings(ggplot2::geom_point(data = x$result, ggplot2::aes(0L, m.diff), stat = "identity", size = point.size)) }
#...................
#### Confidence Intervals ####
if (isTRUE(ci)) { p <- p + suppressWarnings(ggplot2::geom_errorbar(data = x$result, ggplot2::aes(0L, m.diff, ymin = m.low, ymax = m.upp), width = errorbar.width)) }
#...................
#### Jittered Points ####
if (isTRUE(jitter)) { p <- p + suppressWarnings(ggplot2::geom_jitter(data = data.frame(x = x$data$y - x$data$x), ggplot2::aes(x = 0L, y = x), alpha = jitter.alpha, width = jitter.width, height = jitter.height, size = jitter.size)) }
#...................
#### Horizontal Line ####
if (isTRUE(line)) { p <- p + ggplot2::geom_hline(yintercept = 0L, linetype = linetype, linewidth = linewidth) }
})
})
#_____________________________________________________________________________
#
# Save Plot ------------------------------------------------------------------
if (isTRUE(!is.null(filename))) { suppressWarnings(suppressMessages(ggplot2::ggsave(filename = filename, plot = p, width = width, height = height, units = units, dpi = dpi))) }
#_____________________________________________________________________________
#
# Plot -----------------------------------------------------------------------
return(p)
}
#_______________________________________________________________________________
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