multicomp.order
Update a multicomp object by ordering its contrasts.
Update a multicomp object by ordering its contrasts.
The default 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.
- Keywords
- dplot
Usage
multicomp.order(mca, sort.by = "height", sort.order = NULL)multicomp.label.change(x, old="adj", new="new", how.many=2)
# S3 method for multicomp
multicomp.label.change(x, old="adj", new="new", how.many=2)
# S3 method for mmc.multicomp
multicomp.label.change(x, old="adj", new="new", how.many=2)
Arguments
- mca
"multicomp"object. This is the result ofmulticompin S-Plus or the result from applyingas.multicompto a"glht"object in R.- sort.by
Either
"height"or"estimate".- sort.order
Vector of indices by which the contrasts are to be sorted. When
sort.orderin non-NULL, it is used.- x
"multicomp"object.- old
character string to be removed from contrast names.
- new
replacement character string to be inserted in contrast names.
- how.many
number of times to make the replacement.
Value
The result is a "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.
Note
S-Plus use the multicomp functions
and R uses the multcomp package.
References
Heiberger, Richard M. and Holland, Burt (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5.
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.
See Also
MMC, as.glht in R,
multicomp.reverse
Examples
# NOT RUN {
## 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"))
})
# }