#' Panel of Diagnostic Residual Plots.
#'
#' Creates a panel of residual diagnostic plots given a model. Currently accepts
#' models of type "lm", "glm", "lmerMod", "lmerModLmerTest", "lme", and "glmerMod".
#'
#' @param model Model fit using either \code{lm}, \code{glm}, \code{lmer},
#' \code{lmerTest}, \code{lme}, or \code{glmer}.
#' @param plots Plots chosen to include in the panel of plots. The default panel
#' includes a residual plot, a normal quantile plot, an index plot,
#' and a histogram of the residuals. (See details for the options available.)
#' @param type Type of residuals to use in the plot. If not specified, the
#' default residual type for each model type is used. (See details for the
#' options available.)
#' @param bins Number of bins to use when creating a histogram of the residuals.
#' Default is set to 30.
#' @param smoother Indicates whether or not to include a smoother on the index,
#' residual-leverage, location-scale, and residual plots. Specify TRUE or FALSE.
#' Default is set to FALSE.
#' @param qqline Indicates whether to include a 1-1 line on the qq-plot. Specify
#' TRUE or FALSE. Default is set to TRUE.
#' @param qqbands Indicates whether to include confidence bands on the qq-plot.
#' Specify TRUE or FALSE. Default is set to FALSE.
#' @param scale Scales the size of the graphs in the panel. Takes values in (0,1].
#' @param theme ggplot2 theme to be used. Current options are \code{"bw"},
#' \code{"classic"}, and \code{"grey"} (or \code{"gray"}). Default is
#' \code{"bw"}.
#' @param axis.text.size Specifies the size of the text for the axis labels of
#' all plots in the panel.
#' @param title.text.size Specifies the size of the text for the titles of all
#' plots in the panel.
#' @param title.opt Indicates whether or not to include a title on the plots in
#' the panel. Specify TRUE or FALSE. Default is set to TRUE.
#' @param nrow Sets the number of rows in the panel.
#'
#' @export resid_panel
#'
#' @importFrom cowplot plot_grid ggdraw draw_label
#' @importFrom ggplot2 ggplot aes aes_string geom_point geom_abline labs theme_bw theme
#' geom_histogram stat_function xlim geom_boxplot expand_limits geom_smooth
#' element_text ggplotGrob geom_vline theme_classic geom_hline geom_segment
#' geom_line scale_x_continuous scale_y_continuous theme_grey ggplot_build xlab ylab
#' geom_text element_blank
#' @importFrom grDevices extendrange
#' @importFrom MASS stdres
#' @importFrom qqplotr stat_qq_point stat_qq_line stat_qq_band
#' @importFrom stats cooks.distance dnorm fitted hatvalues lowess model.frame resid sd
#' @importFrom stringr str_sub
#'
#' @details
#'
#' The first two sections below contain information on the available input
#' options for the \code{plots} and \code{type} arguments in \code{resid_panel}.
#' The third section contains details relating to the creation of the plots.
#'
#' \strong{Options for Plots}
#'
#' The following options can be chosen for the \code{plots} argument.
#' \itemize{
#' \item "all": This creates a panel of all plot types included in the package
#' that are available for the model type input into \code{resid_panel}. (See note
#' below.)
#' \item "default": This creates a panel with a residual plot, a normal quantile plot
#' of the residuals, an index plot of the residuals, and a histogram of the residuals.
#' \item "R": This creates a panel with a residual plot, a normal
#' quantile plot of the residuals, a location-scale plot, and a residuals versus leverage
#' plot. This was modeled after the plots shown in R if the \code{plot()} base function
#' is applied to an \code{lm} model. This option can only be used with an \code{lm} or
#' \code{glm} model.
#' \item "SAS": This creates a panel with a residual plot, a normal quantile plot of
#' the residuals, a histogram of the residuals, and a boxplot of the residuals.
#' This was modeled after the residualpanel option in proc mixed from SAS version 9.4.
#' \item A vector of individual plots can also be specified.
#' For example, one can specify \code{plots = c("boxplot", "hist")} or
#' \code{plots = "qq"}. The individual plot options are as follows.
#' \itemize{
#' \item \code{"boxplot"}: A boxplot of residuals
#' \item \code{"cookd"}: A plot of Cook's D values versus observation numbers
#' \item \code{"hist"}: A histogram of residuals
#' \item \code{"index"}: A plot of residuals versus observation numbers
#' \item \code{"ls"}: A location scale plot of the residuals
#' \item \code{"qq"}: A normal quantile plot of residuals
#' \item \code{"lev"}: A plot of standardized residuals versus leverage values
#' \item \code{"resid"}: A plot of residuals versus predicted values
#' \item \code{"yvp":}: A plot of observed response values versus predicted values
#' } }
#'
#' Note: \code{"cookd"}, \code{"ls"}, and \code{"lev"} are only available for "lm" and
#' "glm" models.
#'
#' \strong{Options for Type}
#'
#' Several residual types are available to be requested based on the model type
#' that is input into \code{resid_panel}. These currently are as follows.
#' \itemize{
#' \item \code{lm} residual options
#' \itemize{
#' \item \code{"pearson"}:The Pearson residuals
#' \item \code{"response"}: The raw residuals (Default for "lm")
#' \item \code{"standardized"}: The standardized raw residuals
#' }
#' \item \code{glm} residual options
#' \itemize{
#' \item \code{"pearson"}: The Pearson residuals
#' \item \code{"deviance"}: The deviance residuals (Default for "glm")
#' \item \code{"response"}: The raw residuals
#' \item \code{"stand.deviance"}: The standardized deviance residuals
#' \item \code{"stand.pearson"}: The standardized Pearson residuals
#' }
#' \item \code{lmer}, \code{lmerTest}, and \code{lme} residual options
#' \itemize{
#' \item \code{"pearson"}: The Pearson residuals (Default for "lmer", "lmerTest", and "lme")
#' \item \code{"response"}: The raw residuals
#' }
#' \item \code{glmer} residual options
#' \itemize{
#' \item \code{"pearson"}: The Pearson residuals
#' \item \code{"deviance"}: The deviance residuals (Default for "glmer")
#' \item \code{"response"}: The raw residuals
#' } }
#'
#' Note: The plots of \code{"ls"} and \code{"lev"} only accept standardized residuals.
#'
#' \strong{Details on the Creation of Plots}
#'
#' \describe{
#' \item{Boxplot (\code{boxplot})}{Boxplot of the residuals.}
#'
#' \item{Cook's D (\code{cookd})}{ The horizontal line represents a cut-off to identify
#' highly influential points. The horizontal line is placed at 4/n where n is
#' the number of data points used in the \code{model}.}
#'
#' \item{Histogram (\code{hist})}{Plots a histogram of the residuals. The density
#' curve overlaid has mean equal to zero and standard deviation equal to the
#' standard deviation of the residuals.}
#'
#' \item{Index Plot (\code{index})}{Plots the residuals on the y-axis and the observation
#' number associated with the residual on the x-axis.}
#'
#' \item{Residual-Leverage Plot (\code{lev})}{Plots the standardized residuals on the
#' y-axis and the leverage values on the x-axis with a loess curve is overlaid. Cook's
#' D contour lines (which are a function of leverage and standardized residuals) are plotted
#' as the red dashed lines for Cook's D values of 0.5 and 1.}
#'
#' \item{Location-Scale Plot (\code{ls})}{Plots the square root of the absolute value
#' of the standardized residuals on the y-axis and the predicted values on the
#' x-axis. The predicted values are plotted on the original scale for \code{glm}
#' and \code{glmer} models. A loess curve is overlaid.}
#'
#' \item{QQ Plot (\code{qq})}{Makes use of the \code{R} package \code{qqplotr} for
#' creating a normal quantile plot of the residuals.}
#'
#' \item{Residual Plot (\code{resid})}{Plots the residuals on the y-axis and the
#' predicted values on the x-axis. The predicted values are plotted on the
#' original scale for \code{glm} and \code{glmer} models.}
#'
#' \item{Response vs. Predicted (\code{yvp})}{Plots the response variable from the
#' model on the y-axis and the predicted values on the x-axis. Both response
#' variable and predicted values are plotted on the original scale for
#' \code{glm} and \code{glmer} models.}
#'}
#'
#' @return A panel of residual diagnostic plots containing plots specified.
#'
#' @examples
#'
#' # Fit a model to the penguin data
#' penguin_model <- lme4::lmer(heartrate ~ depth + duration + (1|bird), data = penguins)
#'
#' # Create the default panel
#' resid_panel(penguin_model)
#'
#' # Select all plots to include in the panel and set the smoother option to TRUE
#' resid_panel(penguin_model, plots = "all", smoother = TRUE)
#'
#' # Select only the residual plot and qq-plot to be included in the panel,
#' # request confidence bands on the qq plot, and set the number of rows to 2
#' resid_panel(penguin_model, plots = c("resid", "qq"), qqbands = TRUE, nrow = 2)
#'
#' # Choose the SAS panel of plots, change the theme to classic, and remove the
#' # titles of the plots
#' resid_panel(penguin_model, plots = "SAS", theme = "classic", title.opt = FALSE)
resid_panel <- function(model, plots = "default", type = NA, bins = 30,
smoother = FALSE, qqline = TRUE, qqbands = FALSE,
scale = 1, theme = "bw", axis.text.size = 10,
title.text.size = 12, title.opt = TRUE, nrow = NULL){
## Errors and Warnings -------------------------------------------------------
# Checks that return an error
check_modeltype(model = model)
check_residualtype(model = model, type = type)
check_standardized(model = model, plots = plots)
check_cooksd(model = model, plots = plots)
# Checks that return a warning
smoother <- check_smoother(smoother = smoother)
theme <- check_theme(theme = theme)
title.opt <- check_title(title.opt = title.opt)
check_leverage(model = model, plots = plots)
## Creation of plots ---------------------------------------------------------
# Create a boxplot of the residuals if selected in plots otherwise set as NULL
if("boxplot" %in% plots | "SAS" %in% plots | "all" %in% plots){
boxplot <- plot_boxplot(type = type,
model = model,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
boxplot <- NULL
}
# Create a Cook's D plot if selected in plots otherwise set as NULL
if("cookd" %in% plots){
cookd <- plot_cookd(model = model,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else if("all" %in% plots &
!(class(model)[1] %in% c("lme", "lmerMod", "lmerModLmerTest", "glmerMod"))){
cookd <- plot_cookd(model = model,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
cookd <- NULL
}
# Create a histogram of the residuals if selected in plots otherwise set as NULL
if("hist" %in% plots | "default" %in% plots | "SAS" %in% plots | "all" %in% plots){
hist <- plot_hist(model = model,
type = type,
bins = bins,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
hist <- NULL
}
# Create an index plot of the residuals if selected in plots otherwise set as NULL
if("index" %in% plots | "default" %in% plots | "all" %in% plots){
index <- plot_index(model = model,
type = type,
smoother = smoother,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
index <- NULL
}
# Create a residual-leverage plot if selected in plots otherwise set as NULL
if("lev" %in% plots | "R" %in% plots){
lev <- plot_lev(model = model,
type = type,
smoother = smoother,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else if("all" %in% plots &
!(class(model)[1] %in% c("lme", "lmerMod", "lmerModLmerTest", "glmerMod"))){
lev <- plot_lev(model = model,
type = type,
smoother = smoother,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
lev <- NULL
}
# Create a location-scale plot if selected in plots otherwise set as NULL
if("ls" %in% plots | "R" %in% plots){
ls <- plot_ls(model = model,
type = type,
smoother = smoother,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else if("all" %in% plots &
!(class(model)[1] %in% c("lme", "lmerMod", "lmerModLmerTest", "glmerMod"))){
ls <- plot_ls(model = model,
type = type,
smoother = smoother,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
ls <- NULL
}
# Create a q-q plot of the residuals if selected in plots otherwise set as NULL
if("qq" %in% plots | "default" %in% plots | "SAS" %in% plots | "R" %in% plots | "all" %in% plots){
qq <- plot_qq(model = model,
type = type,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt,
qqline = qqline,
qqbands = qqbands)
} else{
qq <- NULL
}
# Create a residual plot if selected in plots otherwise set as NULL
if("resid" %in% plots | "default" %in% plots | "SAS" %in% plots | "R" %in% plots | "all" %in% plots){
resid <- plot_resid(model = model,
type = type,
smoother = smoother,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
resid <- NULL
}
# Create a plot of the response variable vs the predicted values if selected
# in plots otherwise set as NULL
if("yvp" %in% plots | "all" %in% plots){
yvp <- plot_yvp(model = model,
theme = theme,
axis.text.size = axis.text.size,
title.text.size = title.text.size,
title.opt = title.opt)
} else{
yvp <- NULL
}
## Creation of grid of plots -------------------------------------------------
# If individual plots have been specified, set plots equal to "individual"
# Return an error if none of the correct plot options have been specified
if("default" %in% plots | "SAS" %in% plots | "R" %in% plots | "all" %in% plots){
plots <- plots
} else if("boxplot" %in% plots | "cookd" %in% plots | "index" %in% plots |
"hist" %in% plots | "ls" %in% plots | "qq" %in% plots |
"lev" %in% plots | "resid" %in% plots | "yvp" %in% plots){
chosen <- plots
plots <- "individual"
} else{
stop("Invalid plots option entered. See the resid_panel help file for
available options.")
}
# Create a grid of plots based on the plots specified
if (plots == "default"){
# Create grid of the default plots
suppressWarnings(plot_grid(resid, qq, index, hist,
scale = scale, nrow = nrow))
} else if (plots == "SAS"){
# Create grid of SAS plots
suppressWarnings(plot_grid(resid, hist, qq, boxplot,
scale = scale, nrow = nrow))
} else if (plots == "R") {
# Create grid of R plots
suppressWarnings(plot_grid(resid, qq, ls, lev,
scale = scale, nrow = nrow))
} else if (plots == "all") {
# Create grid of all plots
if(class(model)[1] == "lm" | class(model)[1] == "glm"){
# Create the grid
suppressWarnings(plot_grid(resid, index, yvp,
qq, hist, boxplot,
cookd, ls, lev,
scale = scale, nrow = nrow))
} else{
# Create the grid
suppressWarnings(plot_grid(resid, index, yvp,
qq, hist, boxplot,
scale = scale, nrow = nrow))
}
} else if (plots == "individual") {
# Turn the specified plots into a list
individual_plots <- list(boxplot = boxplot,
cookd = cookd,
hist = hist,
index = index,
ls = ls,
qq = qq,
lev = lev,
resid = resid,
yvp = yvp)
# Select the chosen plots
individual_plots <- individual_plots[chosen]
# Create grid of individual plots specified and suppress any warnings
suppressWarnings(plot_grid(plotlist = individual_plots, scale = scale, nrow = nrow))
}
}
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