% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/summary_models.R
\name{summary_models}
\alias{summary_models}
\alias{summary_models.RoBMA}
\alias{print.summary_models.RoBMA}
\title{Summarize Model-Averaged Component Weights}
\usage{
summary_models(object, ...)

\method{summary_models}{RoBMA}(object, type = "marginal", include_mcmc_diagnostics = TRUE, ...)

\method{print}{summary_models.RoBMA}(x, ...)
}
\arguments{
\item{object}{a fitted RoBMA-class product-space object, including
\code{RoBMA}, \code{BMA}/\code{BMA.norm}, and \code{BMA.glmm}.}

\item{...}{additional arguments}

\item{type}{whether to summarize marginal component prior distributions
(\code{"marginal"}) or individual model combinations (\code{"individual"}).}

\item{include_mcmc_diagnostics}{whether to include Bayes factor MCMC
diagnostics in the output. Defaults to \code{TRUE}.}

\item{x}{a \code{summary_models.RoBMA} object.}
}
\value{
A list of class \code{summary_models.RoBMA} with elements
\code{name} and \code{type}. For \code{type = "marginal"}, element
\code{marginal} contains component tables with columns such as
\code{prior_prob}, \code{post_prob}, and \code{inclusion_BF}. For
\code{type = "individual"}, element \code{individual} contains individual
model combinations and posterior probabilities.
}
\description{
Creates marginal or individual model-weight summaries for
RoBMA-class product-space objects.
}
\details{
Only mixture-prior components are summarized; non-mixture
components are omitted.
}
\examples{
\dontrun{
if (requireNamespace("metadat", quietly = TRUE)) {
  data(dat.lehmann2018, package = "metadat")
  fit <- RoBMA(yi = yi, vi = vi, data = dat.lehmann2018, measure = "SMD")

  summary_models(fit)
  summary_models(fit, type = "individual")
}
}

}
