as.multicomp
Support functions in R for MMC (mean--mean multiple comparisons) plots.
MMC plots: In R, functions used to interface the glht
in R to the MMC
functions designed with S-Plus multicomp
notation. These are
all internal functions that the user doesn't see.
- Keywords
- dplot
Usage
## S3 method for class 'mmc.multicomp':
print(x, ...)
## S3 method for class 'multicomp':
print(x, ...)
## print.multicomp.hh(x, digits = 4, ..., height=T) ## S-Plus only
## S3 method for class 'multicomp.hh':
print(x, ...) ## R only
print.glht.mmc.multicomp(x, ...) ## R. yes, spell it out.
as.multicomp(x, ...)
## S3 method for class 'glht':
as.multicomp(x, ## glht object
focus, ## currently required
ylabel=as.character(terms(x$model)[[2]]),
means=model.tables(x$model, type="means",
cterm=focus)$tables[[focus]],
lmat=t(x$linfct),
lmat.rows=-1,
lmat.scale.abs2=TRUE,
estimate.sign=1,
order.contrasts=TRUE,
contrasts.none=FALSE,
level=0.95,
calpha=NULL,
method=x$type,
...
)
as.glht(x, ...)
## S3 method for class 'multicomp':
as.glht(x, ...)
Arguments
- x
"glht"
object foras.multicomp
. A"mmc.multicomp"
object forprint.mmc.multicomp
andprint.glht.mmc.multicomp
. A"multicomp"
object foras.glht
and <- ...
- other arguments.
- focus
- name of focus factor.
- ylabel
- response variable name on the graph.
- means
- means of the response variable on the
focus
factor. - lmat, lmat.rows
mmc
- lmat.scale.abs2
- logical, almost always
TRUE
. If it is notTRUE
, then the contrasts will not be properly placed on the MMC plot. - estimate.sign
- numeric. 1: force all contrasts to be positive by
reversing negative contrasts. $-1$: force all contrasts to be negative by
reversing positive contrasts. Leave contrasts as they are constructed
by
glht
. - order.contrasts
- logical. If
TRUE
, order contrasts byheight
(seeMMC
). - contrasts.none
- logical. This is an internal detail. The
``contrasts'' for the group means are not real contrasts in the
sense they don't compare anything.
glht.mmc.glht
sets this argument toTRUE
for thenone
comp - level
- Confidence level. Defaults to 0.95.
- calpha
- User-specified critical point.
See
confint.glht.hh
andconfint.glht
. - method
- See
type
inconfint.glht
.
Details
The mmc.multicomp
print
method displays the confidence intervals and heights on the
MMC plot for each component of the mmc.multicomp
object.
print.multicomp
displays the confidence intervals and heights for
a single component.
print.glht.mmc.multicomp(x, ...)
uses print.glht
on each
component of a mmc.multicomp
object and therefore prints only
the estimates of the comparisons.
Value
as.multicomp
is a generic function to change its argument to a"multicomp"
object.as.multicomp.glht
changes an"glht"
object to a"multicomp"
object. If the model component of the argument"x"
is an"aov"
object then the standard error is taken from theanova(x$model)
table, otherwise from thesummary(x)
. With a large number of levels for the focus factor, thesummary(x)
function is exceedingly slow (80 minutes for 30 levels on 1.5GHz Windows XP). For the same example, theanova(x$model)
takes a fraction of a second.
Note
The multiple comparisons calculations in R and S-Plus use
completely different libraries.
MMC plots in R are based on glht
.
MMC plots in S-Plus are based on multicomp
.
The MMC plot is the same in both systems. The details of gettting the
plot differ.
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, R.~M. and Holland, B. (2006). "Mean--mean multiple comparison displays for families of linear contrasts." Journal of Computational and Graphical Statistics, 15:937--955.