% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/conditional_effects.R
\name{conditional_predict}
\alias{conditional_predict}
\title{Conditional predictions}
\usage{
conditional_predict(
  object,
  newdata = NULL,
  type = c("response", "link"),
  summary = TRUE,
  probs = c(0.025, 0.5, 0.975)
)
}
\arguments{
\item{object}{An \code{mlumr_fit} object}

\item{newdata}{Data frame of covariate values. If \code{NULL}, uses IPD covariate
means.}

\item{type}{\code{"response"} for probabilities, means, or rates; \code{"link"} for
the fitted linear-predictor scale.}

\item{summary}{Return summary (\code{TRUE}) or full draws (\code{FALSE})}

\item{probs}{Quantiles for summary}
}
\value{
A data frame with predictions for each treatment at each profile
}
\description{
Generate absolute predictions at specific covariate values for both
treatments.
}
\examples{
\dontrun{
conditional_predict(fit)
conditional_predict(fit, newdata = data.frame(age = 60, sex = 1))
}
}
\seealso{
\code{\link[=conditional_effects]{conditional_effects()}} for covariate-conditional treatment
\emph{effects}; \code{\link[=predict.mlumr_fit]{predict.mlumr_fit()}} for population-level predictions.
}
