as.multicomp {HH} | R Documentation |
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.
## 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=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, ...) ## S3 method for class 'multicomp': as.glht(x, ...)
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 print.multicomp . |
... |
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
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 component.
|
level |
Confidence level. Defaults to 0.95. |
calpha |
User-specified critical point.
See confint.glht.hh and
confint.glht . |
df, vcov. |
Arguments forwarded through glht to
modelparm . |
method |
See type in confint.glht . |
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.
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.
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.
Richard M. Heiberger <rmh@temple.edu>
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.
mmc
,
glht
in R,
multicomp
in S-Plus.