Summary information from random effects
This function extracts the different variance components of a mixed model and returns the result as a data frame.
random_parameters(model, component = "conditional")
model |
A mixed effects model (including |
component |
Should all parameters, parameters for the conditional model,
or for the zero-inflated part of the model be returned? Applies to models
with zero-inflated component. |
The variance components are obtained from
get_variance and are denoted as following:
The residual variance, σ2ε, 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 (τ00),
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 (τ11)
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
(ρ01)
is obtained from VarCorr(). This measure is only available
for mixed models with random intercepts and slopes.
Note: For the within-group and between-group variance, variance and standard deviations (which are simply the square root of the variance) are shown.
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.
if (require("lme4")) {
data(sleepstudy)
model <- lmer(Reaction ~ Days + (1 + Days | Subject), data = sleepstudy)
random_parameters(model)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.