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\name{lambda.MD}
\alias{lambda.MD}
\title{Calculate shares using data from MD model}
\description{Calculates the population share of row members in a
particular column as a proportion of the total number of row members in the selected subset of columns.}
\usage{
lambda.MD(object, columns, ret.mcmc = TRUE)
}
\arguments{
\item{object}{an R object of class \code{eiMD}, output from \code{\link{ei.MD.bayes}}}
\item{columns}{a character vector of column names to be included in
calculating the shares}
\item{ret.mcmc}{a logical value indicating how the samples from the posterior
should be returned. If \code{TRUE} (default), samples are returned as \code{mcmc}
objects. If \code{FALSE}, samples are returned as arrays. }
}
\value{
Returns either a ((\eqn{R}{R} * included columns) \eqn{\times}{x}
samples) matrix as an \code{mcmc} object or a (\eqn{R \times}{R x}
included columns \eqn{\times}{x} samples) array.
}
\details{This function allows users to define subpopulations within the
data and calculate the proportion of individuals within each of the
columns that defines that subpopulation. For example, if the model
includes the groups Democrat, Republican, and Unaffiliated, the
argument \code{columns = c(``Democrat", ``Republican")} will calculate
the two-party shares of Democrats and Republicans for each row.
}
\seealso{\code{\link{ei.MD.bayes}}}
\author{
Michael Kellermann <\email{mrkellermann@gmail.com}> and Olivia Lau
<\email{olivia.lau@post.harvard.edu}>
}
\keyword{models}
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