\name{cholesterol}
\alias{cholesterol}
\docType{data}
\title{ Cholesterol Reduction Data Set }
\usage{data("cholesterol")}
\description{
 Cholesterol reduction for five treatments.
}
\format{
  This data frame contains the following variables
  \describe{
    \item{trt}{treatment groups, a factor at levels \code{1time}, \code{2times},
               \code{4times}, \code{drugD} and \code{drugE}.}
    \item{response}{cholesterol reduction.}
  }
}
\details{

  A clinical study was conducted to assess the effect of three formulations
  of the same drug on reducing cholesterol. The formulations were
  20mg at once (\code{1time}), 10mg twice a day (\code{2times}), and 5mg
  four times a day (\code{4times}). In addition, two competing drugs
  were used as control group (\code{drugD} and \code{drugE}). The purpose of 
  the study was to find which of the formulations, if any, is efficacious and how
  these formulations compare with the existing drugs.

}
\source{

  P. H. Westfall, R. D. Tobias, D. Rom, R. D. Wolfinger, Y. Hochberg (1999).
  \emph{Multiple Comparisons and Multiple Tests Using the SAS System}.
  Cary, NC: SAS Institute Inc., page 153.

}
\examples{

  ### adjusted p-values for all-pairwise comparisons in a one-way layout 
  ### set up ANOVA model  
  amod <- aov(response ~ trt, data = cholesterol)

  ### set up multiple comparisons object for all-pair comparisons
  cht <- glht(amod, linfct = mcp(trt = "Tukey"))

  ### cf. Westfall et al. (1999, page 171)
  summary(cht, test = univariate())
  summary(cht, test = adjusted("Shaffer"))
  summary(cht, test = adjusted("Westfall"))

  ### use only a subset of all pairwise hypotheses
  K <- contrMat(table(cholesterol$trt), type="Tukey")
  Ksub <- rbind(K[c(1,2,5),],
                "D - test" = c(-1, -1, -1, 3, 0),
                "E - test" = c(-1, -1, -1, 0, 3))

  ### reproduce results in Westfall et al. (1999, page 172)
  ### note: the ordering of our estimates here is different
  amod <- aov(response ~ trt - 1, data = cholesterol)
  summary(glht(amod, linfct = mcp(trt = Ksub[,5:1])), 
          test = adjusted("Westfall"))
}
\keyword{datasets}
