plot_scat2d: Plot paired observations

In GRousselet/rogme: Robust Graphical Methods For Group Comparisons

Plot paired observations

Description

Scatterplot of paired observations with reference line of no effect. Quartiles of each condition are superimposed. Quartiles are estimated using the Harrell-Davis estimator.

Usage

plot_scat2d(
  df = df,
  formula = cond2 ~ cond1,
  min.x = NA,
  min.y = NA,
  max.x = NA,
  max.y = NA,
  axis.steps = 2,
  size_p = 5,
  stroke_p = 1,
  shape_p = 21,
  colour_p = "black",
  fill_p = "#ffb347",
  alpha_p = 0.5,
  linetype_q = "dashed",
  size_q = 1,
  alpha_q = 0.5,
  colour_q = "black"
)

Arguments

df	Data frame with paired observations in two columns.
formula	A formula with format response variable ∼ predictor variable, where ~ (tilde) means "is modeled as a function of".
min.x, min.y, max.x, max.y	Specify axis limits - default square axes
axis.steps	Steps between x and y tick marks - default = 2.
size_p	Size parameter of the scatterplot - default = 5.
stroke_p	Stroke parameter of the scatterplot - default = 1,
shape_p	Shape parameter of the scatterplot - default = 21,
colour_p	Colour parameter of the scatterplot - default = "black",
fill_p	Fill parameter of the scatterplot - default = "#ffb347",
alpha_p	Alpha parameter of the scatterplot - default = .5,
linetype_q	Linetype of the segments marking the quartiles - default = "dashed",
size_q	Size of the segments marking the quartiles - default = 1,
alpha_q	Alpha of the segments marking the quartiles - default = .5,
colour_q	Colour of the segments marking the quartiles - default = "black"

See Also

hd

Examples

df <- tibble(cond1 = rnorm(50), cond2 = cond1 + rnorm(50))
plot_scat2d(df, formula = cond2 ~ cond1) # basic call
plot_scat2d(df, formula = cond2 ~ cond1, size_q=3) # specify size of quartile segments
plot_scat2d(df, formula = cond2 ~ cond1, size_q=c(1,2,1)) # use thicker line for median
plot_scat2d(df, formula = cond2 ~ cond1, linetype_q = "longdash") # specify linetype - default = dashed

GRousselet/rogme documentation built on Nov. 12, 2022, 4:38 a.m.