resplot: Produce residual plots of linear models

In biometryassist: Functions to Assist Design and Analysis of Agronomic Experiments

Produce residual plots of linear models

Description

Produces plots of residuals for assumption checking of linear (mixed) models.

Usage

resplot(
  model.obj,
  shapiro = TRUE,
  call = FALSE,
  label.size = 10,
  axes.size = 10,
  call.size = 9,
  onepage = FALSE,
  onepage_cols = 3,
  mod.obj
)

Arguments

model.obj	An aov, lm, lme (nlme::lme()), lmerMod (lme4::lmer()), asreml or mmer (sommer) model object.
shapiro	(Logical) Display the Shapiro-Wilk test of normality on the plot? This test is unreliable for larger numbers of observations and will not work with n >= 5000 so will be omitted from any plots.
call	(Logical) Display the model call on the plot?
label.size	A numeric value for the size of the label (A,B,C) font point size.
axes.size	A numeric value for the size of the axes label font size in points.
call.size	A numeric value for the size of the model displayed on the plot.
onepage	(Logical) If TRUE and there are multiple plots, combines up to 6 plots per page.
onepage_cols	Integer. Number of columns to use in grid layout when onepage=TRUE. Default is 3.
mod.obj	Deprecated to be consistent with other functions. Please use model.obj instead.

Value

A ggplot2 object containing the diagnostic plots.

Examples

dat.aov <- aov(Petal.Length ~ Petal.Width, data = iris)
resplot(dat.aov)
resplot(dat.aov, call = TRUE)

biometryassist documentation built on June 11, 2025, 5:08 p.m.