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.
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)
mca |
|
sort.by |
Either |
sort.order |
Vector of indices by which the contrasts are to be
sorted. When |
x |
|
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. |
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 bymmcplot
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.
S-Plus use the multicomp
functions
and R uses the multcomp
package.
Richard M. Heiberger <rmh@temple.edu>
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://www.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.
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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