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This function extracts the different variance components of a mixed model and returns the result as a data frame.
random_parameters(model)
A mixed effects model (including stanreg
models).
A data frame with random effects statistics for the variance components, including number of levels per random effect group, as well as complete observations in the model.
The variance components are obtained from get_variance
and are denoted as following:
The residual variance, , is the sum of the distribution-specific variance and the variance due to additive dispersion. It indicates the within-group variance.
The random intercept variance, or between-group variance
for the intercept (),
is obtained from VarCorr()
. It indicates how much groups
or subjects differ from each other.
The random slope variance, or between-group variance
for the slopes ()
is obtained from VarCorr()
. This measure is only available
for mixed models with random slopes. It indicates how much groups
or subjects differ from each other according to their slopes.
The random slope-intercept correlation
()
is obtained from VarCorr()
. This measure is only available
for mixed models with random intercepts and slopes.
# NOT RUN {
if (require("lme4")) {
data(sleepstudy)
model <- lmer(Reaction ~ Days + (1 + Days | Subject), data = sleepstudy)
random_parameters(model)
}
# }
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