## This example is from Hsu and Peruggia
## This is the S-Plus version
## See ?aovSufficient for R
if.R(r={},
s={
data(pulmonary)
pulmonary.aov <- aovSufficient(FVC ~ smoker,
data=pulmonary)
summary(pulmonary.aov)
## multicomp object
pulmonary.mca <-
multicomp.mean(pulmonary$smoker,
pulmonary$n,
pulmonary$FVC,
pulmonary$s,
ylabel="pulmonary",
focus="smoker")
pulmonary.mca
## lexicographic ordering of contrasts, some positive and some negative
plot(pulmonary.mca)
pulm.lmat <- cbind("npnl-mh"=c( 1, 1, 1, 1,-2,-2), ## not.much vs lots
"n-pnl" =c( 3,-1,-1,-1, 0, 0), ## none vs light
"p-nl" =c( 0, 2,-1,-1, 0, 0), ## {} arbitrary 2 df
"n-l" =c( 0, 0, 1,-1, 0, 0), ## {} for 3 types of light
"m-h" =c( 0, 0, 0, 0, 1,-1)) ## moderate vs heavy
dimnames(pulm.lmat)[[1]] <- row.names(pulmonary)
pulm.lmat
## mmc.multicomp object
pulmonary.mmc <-
multicomp.mmc.mean(pulmonary$smoker,
pulmonary$n,
pulmonary$FVC,
pulmonary$s,
ylabel="pulmonary",
focus="smoker",
lmat=pulm.lmat,
plot=FALSE)
old.omd <- par(omd=c(0,.95, 0,1))
## pairwise comparisons
plot(pulmonary.mmc, print.mca=TRUE, print.lmat=FALSE)
## tiebreaker plot, with contrasts ordered to match MMC plot,
## with all contrasts forced positive and with names also reversed,
## and with matched x-scale.
plotMatchMMC(pulmonary.mmc$mca)
## orthogonal contrasts
plot(pulmonary.mmc)
## pairwise and orthogonal contrasts on the same plot
plot(pulmonary.mmc, print.mca=TRUE, print.lmat=TRUE)
par(old.omd)
})
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