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=deparse(terms(x$model)[[2]]),
means=model.tables(x$model, type="means",
cterm=focus)$tables[[focus]],
height,
lmat=t(x$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,
df,
vcov.,
...
)
as.glht(x, ...)
## S3 method for class 'multicomp':
as.glht(x, ...)
Arguments
x
"glht"
object for as.multicomp
.
A "mmc.multicomp"
object for print.mmc.multicomp
and
print.glht.mmc.multicomp
.
A "multicomp"
object for as.glht
and <
focus
name of focus factor.
ylabel
response variable name on the graph.
means
means of the response variable on the focus
factor.
lmat.scale.abs2
logical, almost always TRUE
. If it is
not TRUE
, 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, height
logical. If TRUE
, order contrasts by
height
(see MMC
). 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 to TRUE
for the none
comp
level
Confidence level. Defaults to 0.95.
df, vcov.
Arguments forwarded through glht
to
modelparm
.