pmm.match.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mice.impute.pmm.R
\name{.pmm.match}
\alias{.pmm.match}
\title{Finds an imputed value from matches in the predictive metric (deprecated)}
\usage{
.pmm.match(z, yhat = yhat, y = y, donors = 5, ...)
}
\arguments{
\item{z}{A scalar containing the predicted value for the current case
to be imputed.}

\item{yhat}{A vector containing the predicted values for all cases with an observed
outcome.}

\item{y}{A vector of \code{length(yhat)} elements containing the observed outcome}

\item{donors}{The size of the donor pool among which a draw is made. The default is
\code{donors = 5}. Setting \code{donors = 1} always selects the closest match. Values
between 3 and 10 provide the best results. Note: This setting was changed from
3 to 5 in version 2.19, based on simulation work by Tim Morris (UCL).}

\item{\dots}{Other parameters (not used).}
}
\value{
A scalar containing the observed value of the selected donor.
}
\description{
This function finds matches among the observed data in the predictive
mean metric. It selects the \code{donors} closest matches, randomly
samples one of the donors, and returns the observed value of the
match.
}
\details{
This function is included for backward compatibility. It was
used up to \code{mice 2.21}. The current \code{mice.impute.pmm()}
function calls the faster \code{C} function \code{matcher} instead of
\code{.pmm.match()}.
}
\references{
Schenker N & Taylor JMG (1996) Partially parametric techniques
for multiple imputation. \emph{Computational Statistics and Data Analysis}, 22, 425-446.

Little RJA (1988) Missing-data adjustments in large surveys (with discussion).
\emph{Journal of Business Economics and Statistics}, 6, 287-301.
}
\author{
Stef van Buuren
}