cholesterol {multcomp}

Cholesterol Reduction Data Set

Description

Cholesterol reduction for five treatments.

Usage

data("cholesterol")

Format

This data frame contains the following variables

trt

treatment groups, a factor at levels 1time, 2times, 4times, drugD and drugE.

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 (1time), 10mg twice a day (2times), and 5mg four times a day (4times). In addition, two competing drugs were used as control group (drugD and 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). 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"))