% 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) # Pinheiro and Bates, pp. 222-225 fm1BW.lme <- lme(weight ~ Time * Diet, BodyWeight, random = ~ Time) # p. 223 fm2BW.lme <- update(fm1BW.lme, weights = varPower()) # 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) ## Print/Summary methods for the empty case: (cCS <- corCompSymm()) # Uninitialized correlation struc.. summary(cCS) # (ditto) } \keyword{models}