Q-Q Plot of Residuals to Assess Normality

Produces a Q-Q plot of residuals from a linear model to test for normality, optionally annotating outlier points and adding the Shapiro-Wilk test p-value.

Usage

lm_plot.qq(
  mdl,
  opt = list(),
  parm = list(),
  df = lm_plot.df(mdl),
  plts = list()
)

Arguments

mdl: A fitted model object (typically from lm).
opt: List of options, where pval.SW (logical, default = FALSE) indicates whether to include Shapiro-Wilk p-value on the plot.
parm: List of plotting parameters, usually from lm_plot.parms().
df: Data frame with augmented model data. Defaults to lm_plot.df(mdl).
plts: List of ggplot objects to which this plot will be added.

Value

A list containing:

mdl Fitted model object,
opt Options used, including pval.SW,
parm Parameter list with Shapiro-Wilk test results added,
df Data frame used for plotting,
plts List of ggplot objects, including the $qq element.

Details

The plot visualizes the distribution of residuals against theoretical normal quantiles. Points are colored and shaped by outlier status, and a reference Q-Q line is added. Optionally, outlier and regular points can be labeled. If enabled, the Shapiro-Wilk normality test p-value is displayed.

Examples

mdl <- lm(Sepal.Length ~ Sepal.Width, data = iris)
result <- lm_plot.qq(mdl)
print(result$plts$qq)