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% File nlme/man/corCompSymm.Rd
% Part of the nlme package for R
% Distributed under GPL 2 or later: see nlme/LICENCE.note
\name{corCompSymm}
\title{Compound Symmetry Correlation Structure}
\usage{
corCompSymm(value, form, fixed)
}
\alias{corCompSymm}
\arguments{
\item{value}{the correlation between any two correlated
observations. Defaults to 0.}
\item{form}{a one sided formula of the form \code{~ t}, or \code{~ t |
g}, specifying a time covariate \code{t} and, optionally, a
grouping factor \code{g}. When a grouping factor is present in
\code{form}, the correlation structure is assumed to apply only
to observations within the same grouping level; observations with
different grouping levels are assumed to be uncorrelated. Defaults to
\code{~ 1}, which corresponds to using the order of the observations
in the data as a covariate, and no groups.}
\item{fixed}{an optional logical value indicating whether the
coefficients should be allowed to vary in the optimization, or kept
fixed at their initial value. Defaults to \code{FALSE}, in which case
the coefficients are allowed to vary.}
}
\description{
This function is a constructor for the \code{corCompSymm} class,
representing a compound symmetry structure corresponding to uniform
correlation. Objects created using this constructor must later be
initialized using the appropriate \code{Initialize} method.
}
\value{
an object of class \code{corCompSymm}, representing a compound
symmetry correlation structure.
}
\references{
Milliken, G. A. and Johnson, D. E. (1992) "Analysis of Messy Data,
Volume I: Designed Experiments", Van Nostrand Reinhold.
Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models
in S and S-PLUS", Springer, esp. pp. 233-234.
}
\author{José Pinheiro and Douglas Bates \email{bates@stat.wisc.edu}}
\seealso{
\code{\link{corClasses}},
\code{\link{Initialize.corStruct}},
\code{\link{summary.corStruct}}
}
\examples{
## covariate is observation order and grouping factor is Subject
cs1 <- corCompSymm(0.5, form = ~ 1 | Subject)
cs1 # Uninitialized ...
\dontshow{summary(cs1) # (ditto)}
# Pinheiro and Bates, p. 225
cs1CompSymm <- corCompSymm(value = 0.3, form = ~ 1 | Subject)
cs2CompSymm <- corCompSymm(value = 0.3, form = ~ age | Subject)
cs1CompSymm <- Initialize(cs1CompSymm, data = Orthodont)
corMatrix(cs1CompSymm)
}
\keyword{models}
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