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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/random_parameters.R
\name{random_parameters}
\alias{random_parameters}
\title{Summary information from random effects}
\usage{
random_parameters(model, component = "conditional")
}
\arguments{
\item{model}{A mixed effects model (including \code{stanreg} models).}
\item{component}{Should all parameters, parameters for the conditional model,
for the zero-inflation part of the model, or the dispersion model be returned?
Applies to models with zero-inflation and/or dispersion component. \code{component}
may be one of \code{"conditional"}, \code{"zi"}, \code{"zero-inflated"}, \code{"dispersion"} or
\code{"all"} (default). May be abbreviated.}
}
\value{
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.
}
\description{
This function extracts the different variance components of a
mixed model and returns the result as a data frame.
}
\details{
The variance components are obtained from \code{\link[insight:get_variance]{insight::get_variance()}} and
are denoted as following:
\subsection{Within-group (or residual) variance}{
The residual variance, \ifelse{html}{\out{σ<sup>2</sup><sub>ε</sub>}}{\eqn{\sigma^2_\epsilon}},
is the sum of the distribution-specific variance and the variance due to additive dispersion.
It indicates the \emph{within-group variance}.
}
\subsection{Between-group random intercept variance}{
The random intercept variance, or \emph{between-group} variance
for the intercept (\ifelse{html}{\out{τ<sub>00</sub>}}{\eqn{\tau_{00}}}),
is obtained from \code{VarCorr()}. It indicates how much groups
or subjects differ from each other.
}
\subsection{Between-group random slope variance}{
The random slope variance, or \emph{between-group} variance
for the slopes (\ifelse{html}{\out{τ<sub>11</sub>}}{\eqn{\tau_{11}}})
is obtained from \code{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.
}
\subsection{Random slope-intercept correlation}{
The random slope-intercept correlation
(\ifelse{html}{\out{ρ<sub>01</sub>}}{\eqn{\rho_{01}}})
is obtained from \code{VarCorr()}. This measure is only available
for mixed models with random intercepts and slopes.
\strong{Note:} For the within-group and between-group variance, variance
and standard deviations (which are simply the square root of the variance)
are shown.
}
}
\examples{
if (require("lme4")) {
data(sleepstudy)
model <- lmer(Reaction ~ Days + (1 + Days | Subject), data = sleepstudy)
random_parameters(model)
}
}
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