plot_qqmodel: Plot quantile-quantile (QQ) graphs from residuals of linear...

In grafify: Easy Graphs for Data Visualisation and Linear Models for ANOVA

Plot quantile-quantile (QQ) graphs from residuals of linear models.

Description

This function takes a linear model (simple or mixed effects) and plots a QQ graph after running rstudent from rstudent to generate a table of Studentised model residuals on an ordinary (simple_model), mixed model (mixed_model or mixed_model_slopes. The graph plots studentised residuals from the model (sample) on Y axis & Theoretical quantiles on X axis.

Usage

plot_qqmodel(
  Model,
  symsize = 3,
  s_alpha = 0.8,
  fontsize = 20,
  symthick,
  linethick,
  SingleColour = "#E69F00"
)

Arguments

Model	name of a saved model generated by simple_model or mixed_model.
symsize	size of symbols, default set to 3.
s_alpha	fractional opacity of symbols, default set to 0.8 (i.e., 80% opacity).
fontsize	parameter of base_size of fonts in theme_classic, default set to size 20.
symthick	thickness of symbol border, default set to fontsize/22.
linethick	thickness of line, default set to fontsize/22.
SingleColour	colour of symbols (default = ⁠#E69F00⁠, which is ok_orange)

Details

For generalised additive models fit with mgcv, scaled Pearson residuals are plotted.

The function uses ggplot2[geom_qq] and ggplot2[geom_qq_line] geometries. Symbols receive "ok_orange" colour by default.

Value

This function returns a ggplot2 object of class "gg" and "ggplot".

Examples

#Basic usage
m1 <- simple_model(data = data_2w_Festing, 
Y_value = "GST", 
Fixed_Factor = c("Treatment", "Strain"))
plot_qqmodel(m1)

grafify documentation built on May 29, 2024, 3:49 a.m.