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\name{deff}
\alias{deff}
\title{
Design Effect and Intra-cluster Correlation
}
\description{
Computes the Kish design effect and corresponding intra-cluster correlation
for a single cluster-sampled variable
}
\usage{
deff(y, cluster)
}
\arguments{
\item{y}{
variable to analyze
}
\item{cluster}{
a variable whose unique values indicate cluster membership. Any
type of variable is allowed.
}
}
\value{
a vector with named elements \code{n} (total number of non-missing
observations), \code{clusters} (number of clusters after deleting
missing data), \code{rho}(intra-cluster correlation), and \code{deff}
(design effect).
}
\author{
Frank Harrell
\cr
Department of Biostatistics
\cr
Vanderbilt University
\cr
\email{fh@fharrell.com}
}
\seealso{
\code{\link[rms]{bootcov}}, \code{\link[rms]{robcov}}
}
\examples{
set.seed(1)
blood.pressure <- rnorm(1000, 120, 15)
clinic <- sample(letters, 1000, replace=TRUE)
deff(blood.pressure, clinic)
}
\keyword{htest}
\concept{study design}
\concept{cluster sampling}
|
