
sort.by = "height"
matches the order in the MMC plot.
An alternate sort.by = "estimate"
matches the order of the
half-normal plot. Or the argument sort.order
can be used
to specify any other order.multicomp.order(mca, sort.by = "height", sort.order = NULL)multicomp.label.change(x, old="adj", new="new", how.many=2)
## S3 method for class 'multicomp':
multicomp.label.change(x, old="adj", new="new", how.many=2)
## S3 method for class 'mmc.multicomp':
multicomp.label.change(x, old="adj", new="new", how.many=2)
"multicomp"
object. This is the result of
multicomp
in S-Plus or the result from applying as.multicomp
to
a "glht"
object in R."height"
or "estimate"
.sort.order
in non-NULL
, it is used."multicomp"
object."multicomp"
object containing the same
contrasts as the argument.
multicomp.order
sorts the contrasts
(and renames them consistently) according to the specifications.
multicomp.label.change
changes the contrast names according to the specifications.When sort.by=="height"
, sort the contrasts by the reverse order
of the heights. This provides a "multicomp"
object that will be
plotted by plot.multicomp
in the same order used by
mmcplot
or the older plot.mmc.multicomp
. If there is not "height"
component,
the original "multicomp"
object is returned.
When sort.by=="estimate"
, sort the contrasts by the reverse order
of the contrast estimates. This provides the same order as the
half-normal plot.
When sort.order
in non-NULL
, sort the contrasts in
that order.
Heiberger, Richard M. and Holland, Burt (2006). "Mean--mean multiple comparison displays for families of linear contrasts." Journal of Computational and Graphical Statistics, 15:937--955.
MMC
, as.glht in R
,
multicomp.reverse
## continue with the example in mmc in R, or multicomp.mmc in S-Plus
data(catalystm)
catalystm1.aov <- aov(concent ~ catalyst, data=catalystm)
if.R(r={
catalystm.mca <-
glht(catalystm1.aov, linfct = mcp(catalyst = "Tukey"))
print(confint(catalystm.mca))
catalystm.mmc <-
mmc(catalystm1.aov, linfct = mcp(catalyst = "Tukey"))
## the contrasts have been ordered by height (see ?MMC),
## which in this example corresponds to sort.order=c(1,2,4,3,5,6),
## and reversed, to make the contrast Estimates positive.
print(as.glht(catalystm.mmc$mca))
## ## For consistency with the S-Plus example,
## ## we change all factor level "A" to "control".
## as.glht(multicomp.label.change(catalystm.mmc$mca, "A", "control"))
},s={
catalystm.mca <-
multicomp(catalystm1.aov, method="Tukey")
print(catalystm.mca)
catalystm.mmc <-
multicomp.mmc(catalystm1.aov, method="Tukey", plot=FALSE)
## the contrasts have been ordered by height (see ?MMC),
## which in this example corresponds to sort.order=c(1,2,4,3,5,6),
## and reversed, to make the contrast Estimates positive.
print(catalystm.mmc$mca)
## S-Plus multicomp already uses simple names. This function is
## therefore used in more complex two-way ANOVA examples. We illustrate
## here by changing all factor level "A" to "control".
print(multicomp.label.change(catalystm.mmc$mca, "A", "control"))
})
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