glht
in R to the MMC
functions designed with S-Plus multicomp
notation. These are
all internal functions that the user doesn't see.
"print"(x, ..., width.cutoff=options()$width-5)
"print"(x, ...)
## print.multicomp.hh(x, digits = 4, ..., height=T) ## S-Plus only
"print"(x, ...) ## R only
as.multicomp(x, ...)
"as.multicomp"(x, ## glht object focus=x$focus, ylabel=deparse(terms(x$model)[[2]]), means=model.tables(x$model, type="means", cterm=focus)$tables[[focus]], height=rev(1:nrow(x$linfct)), lmat=t(x$linfct), lmat.rows=lmatRows(x, focus), lmat.scale.abs2=TRUE, estimate.sign=1, order.contrasts=TRUE, contrasts.none=FALSE, level=0.95, calpha=NULL, method=x$type, df, vcov., ... )
as.glht(x, ...)
"as.glht"(x, ...)
"glht"
object for as.multicomp
.
A "mmc.multicomp"
object for print.mmc.multicomp
.
A "multicomp"
object for as.glht
and print.multicomp
.focus
factor.TRUE
. If it is
not TRUE
, then the contrasts will not be properly placed
on the MMC plot.glht
.TRUE
, order contrasts by
height
(see mmc
).mmc.glht
sets this
argument to TRUE
for the none
component.
S-Plus
confint.glht
.
S-Plus
confint.glht
.
glht
to S-Plus
modelparm
.
S-Plus
modelparm
.
type
in S-Plus
confint.glht
.
S-Plus
confint.glht
.
deparse
.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 the
anova(x$model)
table, otherwise from the summary(x)
.
With a large number of levels for the focus factor, the
summary(x)
function is exceedingly slow (80 minutes for 30 levels on 1.5GHz Windows
XP).
For the same example, the anova(x$model)
takes a fraction of
a second.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.
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
,