HH (version 3.1-47)

multicomp.order: Update a multicomp object by ordering its contrasts.

Description

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.

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 of multicomp in S-Plus or the result from applying as.multicomp to 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.order in 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.

References

Heiberger, Richard M. and Holland, Burt (2015). Statistical Analysis and Data Display: An Intermediate Course with Examples in R. Second Edition. Springer-Verlag, New York. https://link.springer.com/us/book/9781493921218

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"))
})

# }