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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 correlatedobservations. 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, agrouping factor \code{g}. When a grouping factor is present in\code{form}, the correlation structure is assumed to apply onlyto observations within the same grouping level; observations withdifferent grouping levels are assumed to be uncorrelated. Defaults to\code{~ 1}, which corresponds to using the order of the observationsin the data as a covariate, and no groups.}\item{fixed}{an optional logical value indicating whether thecoefficients should be allowed to vary in the optimization, or keptfixed at their initial value. Defaults to \code{FALSE}, in which casethe coefficients are allowed to vary.}}\description{This function is a constructor for the \code{corCompSymm} class,representing a compound symmetry structure corresponding to uniformcorrelation. Objects created using this constructor must later beinitialized using the appropriate \code{Initialize} method.}\value{an object of class \code{corCompSymm}, representing a compoundsymmetry 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 Modelsin 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 Subjectcs1 <- corCompSymm(0.5, form = ~ 1 | Subject)cs1 # Uninitialized ...\dontshow{summary(cs1) # (ditto)}# Pinheiro and Bates, p. 225cs1CompSymm <- corCompSymm(value = 0.3, form = ~ 1 | Subject)cs2CompSymm <- corCompSymm(value = 0.3, form = ~ age | Subject)cs1CompSymm <- Initialize(cs1CompSymm, data = Orthodont)corMatrix(cs1CompSymm)}\keyword{models}