% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/naive.R
\name{naive}
\alias{naive}
\title{Naive unadjusted indirect comparison}
\usage{
naive(data, link = NULL, conf_level = 0.95)
}
\arguments{
\item{data}{An \code{mlumr_data} object from \code{\link[=combine_data]{combine_data()}}}

\item{link}{Link function. For binomial: \code{"logit"} (default), \code{"probit"},
or \code{"cloglog"}. For normal/poisson: ignored (identity/log always used).
If \code{NULL}, uses the canonical default.}

\item{conf_level}{Confidence level for the interval (default 0.95)}
}
\value{
An object of class \code{mlumr_naive}
}
\description{
Compute an unadjusted (naive) indirect treatment comparison by comparing
crude outcomes from the IPD and AgD without any covariate adjustment.
Returns treatment effect on the link scale plus absolute predictions
(event probabilities, risk difference, risk ratio) for both populations.
}
\details{
For binomial outcomes, event-probability intervals use Wald standard errors
and are bounded to \verb{[0, 1]}. For Poisson outcomes, the log-rate contrast
uses a 0.5 continuity correction when an observed event count is zero.
}
\examples{
\dontrun{
result <- naive(dat)
print(result)
}
}
