as.multicomp: Support functions in R for MMC (mean-mean multiple...

Description Usage Arguments Details Value Note Author(s) References See Also

Description

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.

Usage

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## 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, ...)

Arguments

x

"glht" object for as.multicomp. A "mmc.multicomp" object for print.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. mmc.glht sets this argument to TRUE for the none component.

level

Confidence level. Defaults to 0.95.

calpha

R only. User-specified critical point. See confint.glht.

df, vcov.

R only. Arguments forwarded through glht to modelparm.

method

R only. See type in confint.glht.

width.cutoff

See deparse.

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.

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 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.

Note

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.

Author(s)

Richard M. Heiberger <rmh@temple.edu>

References

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://www.springer.com/us/book/9781493921218

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.

See Also

mmc, glht.


HH documentation built on Nov. 28, 2020, 9:06 a.m.

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