as.multicomp | 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, ..., width.cutoff=options()$width-5)
## S3 method for class 'multicomp'
print(x, ...)
## print.multicomp.hh(x, digits = 4, ..., height=T) ## S-Plus only
## S3 method for class 'multicomp.hh'
print(x, ...) ## R only
as.multicomp(x, ...)
## S3 method for class 'glht'
as.multicomp(x, ## glht object
focus=x$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, ...)
## S3 method for class 'multicomp'
as.glht(x, ...)
x |
|
... |
other arguments. |
focus |
name of focus factor. |
ylabel |
response variable name on the graph. |
means |
means of the response variable on the |
lmat , lmat.rows |
|
lmat.scale.abs2 |
logical, almost always |
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 |
order.contrasts , height |
logical. If |
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. |
level |
Confidence level. Defaults to 0.95. |
calpha |
R only. User-specified critical point.
See
|
df , vcov. |
R only. Arguments forwarded through |
method |
R only. See |
width.cutoff |
See |
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.
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 functions.
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 (2015). Statistical Analysis and Data Display: An Intermediate Course with Examples in R. Second Edition. Springer-Verlag, New York. https://link.springer.com/book/10.1007/978-1-4939-2122-5
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
,
glht
.
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