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## The cc176 data comes from Cochran and Cox, page 176
## Cochran, W. G. and Cox, G. M. (1957).
## Experimental Designs, Wiley.
if.R(r=
old.contr <- options(contrasts=c("contr.treatment", "contr.treatment"))
,s={})
data(cc176)
current.levels <- c("galvanic","faradic","60.cycle","25.cycle")
cc176 <-
data.frame(wt.d=cc176[,1],
wt.n=cc176[,2],
n.treats=ordered(rep(c(1,3,6), length=96)),
current=ordered(rep(rep(current.levels,
rep(3,4)),8), levels=current.levels),
minutes=ordered(rep(rep(c(1,2,3,5),rep(12,4)), 2)),
rep=rep(c("I","II"), c(48,48)))
contrasts(cc176$n.treats)
contrasts(cc176$n.treats) <-
if.R(s=
contr.poly(c(1,3,6))
,r=
contr.poly(3, scores=c(1,3,6))
)
contrasts(cc176$n.treats)
if.R(r={
contrasts(cc176$current) <- "contr.treatment"
contrasts(cc176$n.treats) <- "contr.treatment"
}
,s={})
if.R(r=
options(old.contr)
,s={})
cc176.aov <- aov(wt.d ~ rep + wt.n + n.treats + wt.n*current, data=cc176)
summary(cc176.aov)
summary(cc176.aov,
split=list(n.treats=list(n.treats.lin=1, n.treats.quad=2)),
expand.split=FALSE)
## almost MMC Figure 3, mmc plot of current, default settings for display
if.R(s={
old.par <- par(mar=c(5,4,4,8)+.1)
cc176.mmc <-
multicomp.mmc(cc176.aov, focus="current",
ry=c(56,72), x.offset=1.5,
valid.check=FALSE, ## Tukey method (slightly narrower bounds)
plot=FALSE)
print(cc176.mmc)
plot(cc176.mmc)
par(old.par)
}
,r={
cc176.mmc <-
mmc(cc176.aov, linfct=mcp(current="Tukey",
`covariate_average`=TRUE, `interaction_average`=TRUE))
print(cc176.mmc)
plot(cc176.mmc)
})
## MMC Figure 3, mmc plot of current, control of display parameters
if.R(
s={
old.par <- par(mar=c(5,4,4,8)+.1)
plot(cc176.mmc, iso.name=FALSE, col.iso=16,
print.mca=TRUE, print.lmat=FALSE)
par(old.par)
},r={
old.par <- par(mar=c(15,4,4,8)+.1)
plot(cc176.mmc, x.offset=1.5,
iso.name=FALSE, col.iso=16,
col.mca.signif="red", lty.mca.not.signif=2,
print.mca=TRUE, print.lmat=FALSE)
par(old.par)
})
## MMC Figure 4, current with orthogonal contrasts and control of display
cc176.orth <- cbind( "g-f"=c( 1,-1, 0, 0),
"60-25"=c( 0, 0, 1,-1),
"gf-AC"=c( 1, 1,-1,-1))
dimnames(cc176.orth)[[1]] <- levels(cc176$current)
if.R(s={
cc176.mmc <-
multicomp.mmc(cc176.aov, focus="current", method="tukey",
focus.lmat=cc176.orth, valid.check=FALSE,
plot=FALSE)
## ry=c(56,72), x.offset=1.5,
print(cc176.mmc)
old.par <- par(mar=c(5,4,4,8)+.1)
plot(cc176.mmc, iso.name=FALSE, col.iso=16,
col.mca.signif="red", lty.mca.not.signif=2,
print.mca=FALSE, print.lmat=TRUE)
par(old.par)
}
,r={
cc176.mmc <-
mmc(cc176.aov,
linfct=mcp(current="Tukey",
`covariate_average`=TRUE, `interaction_average`=TRUE),
focus.lmat=cc176.orth,
)
print(cc176.mmc)
old.par <- par(mar=c(15,4,4,8)+.1)
plot(cc176.mmc, x.offset=1.5,
iso.name=FALSE, col.iso=16,
col.mca.signif="red", lty.mca.not.signif=2,
col.lmat.signif="blue", lty.lmat.not.signif=2,
print.mca=FALSE, print.lmat=TRUE)
par(old.par)
})
## MMC Figure 10, current, pairwise and orthogonal contrasts
if.R(
s={
old.par <- par(mar=c(5,4,4,8)+.1)
plot(cc176.mmc, iso.name=FALSE, col.iso=16,
print.mca=TRUE, print.lmat=TRUE,
col.lmat.signif=6)
par(old.par)
},r={
old.par <- par(mar=c(15,4,4,8)+.1)
plot(cc176.mmc, x.offset=1.5,
iso.name=FALSE, col.iso=16,
col.mca.signif="red", lty.mca.not.signif=2,
col.lmat.signif="blue", lty.lmat.not.signif=2,
print.mca=TRUE, print.lmat=TRUE)
par(old.par)
})
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