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\name{growthcurve}
\alias{compareGrowthCurves}
\alias{compareTwoGrowthCurves}
\alias{plotGrowthCurves}
\title{Compare Groups of Growth Curves}
\description{
Do all pairwise comparisons between groups of growth curves using a permutation test.
}
\usage{
compareGrowthCurves(group, y, levels=NULL, nsim=100, fun=meanT, times=NULL,
verbose=TRUE, adjust="holm")
compareTwoGrowthCurves(group, y, nsim=100, fun=meanT)
plotGrowthCurves(group, y, levels=sort(unique(group)), times=NULL, col=NULL,...)
}
\arguments{
\item{group}{vector or factor indicating group membership. Missing values are allowed in \code{compareGrowthCurves} but not in \code{compareTwoGrowthCurves}.}
\item{y}{matrix of response values with rows for individuals and columns for times. The number of rows must agree with the length of \code{group}. Missing values are allowed.}
\item{levels}{a character vector containing the identifiers of the groups to be compared. By default all groups with two more more members will be compared.}
\item{nsim}{number of permutations to estimated p-values.}
\item{fun}{a function defining the statistic used to measure the distance between two groups of growth curves.
Defaults to \code{\link{meanT}}.}
\item{times}{a numeric vector containing the column numbers on which the groups should be compared.
By default all the columns are used.}
\item{verbose}{should progress results be printed?}
\item{adjust}{method used to adjust for multiple testing, see \code{p.adjust}.}
\item{col}{vector of colors corresponding to distinct groups}
\item{...}{other arguments passed to \code{plot()}}
}
\details{
\code{compareTwoGrowthCurves} performs a permutation test of the difference between two groups of growth curves.
\code{compareGrowthCurves} does all pairwise comparisons between two or more groups of growth curves.
Accurate p-values can be obtained by setting \code{nsim} to some large value, \code{nsim=10000} say.
}
\value{
\code{compareTwoGrowthCurves} returns a list with two components, \code{stat} and \code{p.value}, containing the observed statistics and the estimated p-value. \code{compareGrowthCurves} returns a data frame with components
\item{Group1}{name of first group in a comparison}
\item{Group2}{name of second group in a comparison}
\item{Stat}{observed value of the statistic}
\item{P.Value}{estimated p-value}
\item{adj.P.Value}{p-value adjusted for multiple testing}
}
\author{Gordon Smyth}
\references{
Elso, C. M., Roberts, L. J., Smyth, G. K., Thomson, R. J., Baldwin, T. M.,
Foote, S. J., and Handman, E. (2004). Leishmaniasis host response loci
(lmr13) modify disease severity through a Th1/Th2-independent pathway.
\emph{Genes and Immunity} 5, 93-100.
\url{http://www.nature.com/gene/journal/v5/n2/full/6364042a.html}
Baldwin, T., Sakthianandeswaren, A., Curtis, J., Kumar, B., Smyth, G. K., Foote, S., and Handman, E. (2007).
Wound healing response is a major contributor to the severity of cutaneous leishmaniasis in the ear model of infection.
\emph{Parasite Immunology} 29, 501-513. \url{http://www.blackwell-synergy.com/doi/abs/10.1111/j.1365-3024.2007.00969.x}
}
\seealso{
\code{\link{meanT}}, \code{\link{compareGrowthCurves}}, \code{\link{compareTwoGrowthCurves}}
}
\examples{
# A example with only one time
data(PlantGrowth)
compareGrowthCurves(PlantGrowth$group,as.matrix(PlantGrowth$weight))
# Can make p-values more accurate by nsim=10000
}
\keyword{regression}
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