rrPlot: Residual-Residual Plot

In psre: Presenting Statistical Results Effectively

Residual-Residual Plot

Description

Produces a linear scatterplot array with marginal histograms. The plots have OLS regression lines and a 45-degree line.

Usage

rrPlot(
  formula,
  xlabels = NULL,
  ylab = NULL,
  data,
  return = c("grid", "grobs"),
  ptsize = 1,
  ptshape = 1,
  ptcol = "gray65"
)

Arguments

formula	Formula giving the variables to be plotted.
xlabels	Vector of character strings giving the labs of variables to be used in place of the variable names.
ylab	Character string giving y-variable label to be used instead of variable name.
data	A data frame that holds the variables to be plotted.
return	A string identify what to return. If ‘grid’, then a cowplot object is returned with all plots printed. If ‘grobs’ then a list with all of the individual ggplots/grobs is returned.
ptsize	Size of points.
ptshape	Shape of points.
ptcol	Color of points.

Value

A cowplot object.

Examples

data(wvs)
library(MASS)
lmod <- lm(secpay ~ gini_disp + democrat + log(pop), data=wvs)
e1_m <- rlm(secpay ~ gini_disp + democrat + log(pop), 
                  data=wvs, method="M")$residuals
e1_mm <- rlm(secpay ~ gini_disp + democrat + log(pop), 
                   data=wvs, method="MM")$residuals
e1dat <- data.frame(OLS = lmod$residuals, 
                    M = e1_m, 
                    MM = e1_mm)
rrPlot(OLS ~ M + MM, data=e1dat)

psre documentation built on Aug. 8, 2022, 5:05 p.m.