plot.R2: Visualize standardized effect sizes and model R squared

In bcjaeger/r2glmm: Computes R Squared for Mixed (Multilevel) Models

Visualize standardized effect sizes and model R squared

Description

Visualize standardized effect sizes and model R squared

Usage

## S3 method for class 'R2'
plot(
  x,
  y = NULL,
  txtsize = 10,
  maxcov = 3,
  r2labs = NULL,
  r2mthd = "sgv",
  cor = TRUE,
  ...
)

Arguments

x	An R2 object from the r2beta function.
y	An R2 object from the r2beta function.
txtsize	The text size of the axis labels.
maxcov	Maximum number of covariates to include in the semi-partial plots.
r2labs	a character vector containing labels for the models. The labels are printed as subscripts on a covariance model matrix.
r2mthd	The method used to compute R2
cor	An argument to be passed to the r2dt function. Only relevant if comparing two R2 objects.
...	Arguments to be passed to plot

Value

A visual representation of the model and semi-partial R squared from the r2 object provided.

Examples

library(nlme)
library(r2glmm)

data(Orthodont)

# Linear mixed model
lmemod = lme(distance ~ age*Sex, random = ~1|Subject, data = Orthodont)

r2 = r2beta(model=lmemod,partial=TRUE,method='sgv')

plot(x=r2)

bcjaeger/r2glmm documentation built on June 10, 2025, 8:28 p.m.