varCompare: Compares variance explained for two mixed effects models

In mlmtools: Multi-Level Model Assessment Kit

Compares variance explained for two mixed effects models

Description

Compares variance explained by additional fixed effects for two lme4-fitted mixed-effects models.

Usage

varCompare(model1, model2)

Arguments

model1	A linear mixed-effects model of class lmerMod or lmerModLmerTest
model2	A linear mixed-effects model of class lmerMod or lmerModLmerTest

Details

Specifically, 1-(total variance for less parsimonious model/total variance for more parsimonious model).

Value

Computes the percent increase in variance explained by the less parsimonious (more complicated) model compared to the more parsimonious (less complicated) model.

References

Snijders, T. A. B. & Bosker, R. J. (2012). Multilevel Analysis (2nd Ed.). Sage Publications Ltd.

Examples

# Read in data
data(instruction)
# Create null model
mod0 <- lme4::lmer(mathgain ~ (1 | classid), data = instruction)
# Create model of interest
mod1 <- lme4::lmer(mathgain ~ mathkind + (1 | classid), data = instruction)
# Compare variance explained
### To repress output: use invisible()
varCompare(mod0, mod1)

mlmtools documentation built on Oct. 26, 2022, 9:05 a.m.