Panel of Diagnostic Residual Plots Across Multiple Models.

Creates a panel of residual diagnostic plots given a list of models. Currently accepts models of type "lm", "glm", "lmerMod", "lmerModLmerTest", and "glmerMod".

resid_compare(
  models,
  plots = "default",
  type = NA,
  bins = 30,
  smoother = FALSE,
  qqline = TRUE,
  qqbands = FALSE,
  scale = 1,
  theme = "bw",
  axis.text.size = 10,
  title.text.size = 12,
  title.opt = TRUE,
  nrow = NULL
)

Arguments

models: List of models fit using either lm, glm, lmer, lmerTest, or glmer.
plots: Plots chosen to include in the panel of plots. The default panel includes a residual plot, a normal quantile plot, an index plot, and a histogram of the residuals. (See details for the options available.)
type: Type of residuals to use in the plot. If not specified, the default residual type for each model type is used. (See details for the options available.)
bins: Number of bins to use when creating a histogram of the residuals. Default is set to 30.
smoother: Indicates whether or not to include a smoother on the index, residual-leverage, location-scale, and residual plots. Specify TRUE or FALSE. Default is set to FALSE.
qqline: Indicates whether to include a 1-1 line on the qq-plot. Specify TRUE or FALSE. Default is set to TRUE.
qqbands: Indicates whether to include confidence bands on the qq-plot. Specify TRUE or FALSE. Default is set to FALSE.
scale: Scales the size of the graphs in the panel. Takes values in (0,1].
theme: ggplot2 theme to be used. Current options are "bw", "classic", and "grey" (or "gray"). Default is "bw".
axis.text.size: Specifies the size of the text for the axis labels of all plots in the panel.
title.text.size: Specifies the size of the text for the titles of all plots in the panel.
title.opt: Indicates whether or not to include a title on the plots in the panel. Specify TRUE or FALSE. Default is set to TRUE.
nrow: Sets the number of rows in the panel.

Value

A panel of residual diagnostic plots containing plots specified for each model.

Details

The first two sections below contain information on the available input options for the plots and type arguments in resid_compare. The third section contains details relating to the creation of the plots.

Options for Plots

The following options can be chosen for the plots argument.

"all": This creates a panel of all plot types included in the package that are available for the model type input into residpanel. (See note below.)
"default": This creates a panel with a residual plot, a normal quantile plot of the residuals, an index plot of the residuals, and a histogram of the residuals.
"R": This creates a panel with a residual plot, a normal quantile plot of the residuals, a location-scale plot, and a leverage versus residuals plot. This was modeled after the plots shown in R if the plot() base function is applied to an lm model. This option can only be used with an lm or glm model.
"SAS": This creates a panel with a residual plot, a normal quantile plot of the residuals, a histogram of the residuals, and a boxplot of the residuals. This was modeled after the residpanel option in proc mixed from SAS version 9.4.
A vector of individual plots can also be specified. For example, one can specify plots = c("boxplot", "hist") or plots = "qq". The individual plot options are as follows.
- "boxplot": A boxplot of residuals
- "cookd": A plot of Cook's D values versus observation numbers
- "hist": A histogram of residuals
- "index": A plot of residuals versus observation numbers
- "ls": A location scale plot of the residuals
- "qq": A normal quantile plot of residuals
- "lev": A plot of leverage values versus residuals
- "resid": A plot of residuals versus predicted values
- "yvp":: A plot of observed response values versus predicted values

Note: "cookd", "ls", and "lev" are only available for "lm" and "glm" models.

Options for Type

Several residual types are available to be requested based on the model type that is input into resid_panel. These currently are as follows.

lm residual options
- "pearson":The Pearson residuals
- "response": The raw residuals (Default for "lm")
- "standardized": The standardized raw residuals
glm residual options
- "pearson": The Pearson residuals
- "deviance": The deviance residuals (Default for "glm")
- "response": The raw residuals
- "stand.deviance": The standardized deviance residuals
- "stand.pearson": The standardized Pearson residuals
lmer, lmerTest, and lme residual options
- "pearson": The Pearson residuals (Default for "lmer", "lmerTest", and "lme")
- "response": The raw residuals
glmer residual options
- "pearson": The Pearson residuals
- "deviance": The deviance residuals (Default for "glmer")
- "response": The raw residuals

Note: The plots of "ls" and "lev" only accept standardized residuals.

Details on the Creation of Plots

Boxplot (boxplot): Boxplot of the residuals.
Cook's D (cookd): The horizontal line represents a cut-off to identify highly influential points. The horizontal line is placed at 4/n where n is the number of data points used in the model.
Histogram (hist): Plots a histogram of the residuals. The density curve overlaid has mean equal to zero and standard deviation equal to the standard deviation of the residuals.
Index Plot (index): Plots the residuals on the y-axis and the observation number associated with the residual on the x-axis.
Leverage Plot (lev): Plots the standardized residuals on the y-axis and the leverage values on the x-axis. A lowess curve is overlaid, and Cook's D contours are included for \(\alpha = 0.5\) and \(\alpha = 1\).
Location-Scale Plot (ls): Plots the square root of the absolute value of the standardized residuals on the y-axis and the predicted values on the x-axis. The predicted values are plotted on the original scale for glm and glmer models. A lowess curve is overlaid.
QQ Plot (qq): Makes use of the R package qqplotr for creating a normal quantile plot of the residuals.
Residual Plot (resid): Plots the residuals on the y-axis and the predicted values on the x-axis. The predicted values are plotted on the original scale for glm and glmer models.
Response vs. Predicted (yvp): Plots the response variable from the model on the y-axis and the predicted values on the x-axis. Both response variable and predicted values are plotted on the original scale for glm and glmer models.

Examples


# Fit two models to the penguins data
penguin_model <- lme4::lmer(heartrate ~ depth + duration + (1|bird), data = penguins)
penguin_model_log2 <- lme4::lmer(log(heartrate) ~ depth + duration + I(duration^2) +
(1|bird), data = penguins)

# Compare the residuals from the model
resid_compare(list(penguin_model, penguin_model_log2))


# Adjust some options in the panel of plots
resid_compare(list(penguin_model, penguin_model_log2), plots = c("resid", "yvp"),
smoother = TRUE, theme = "grey")
#> `geom_smooth()` using formula 'y ~ x'
#> `geom_smooth()` using formula 'y ~ x'