HH (version 3.1-37)

mmcplot: MMC (Mean-mean Multiple Comparisons) plots in lattice.

Description

MMC (Mean--mean Multiple Comparisons) plots in lattice

Usage

mmcplot(mmc, ...)
# S3 method for mmc
mmcplot(mmc, col=col, lwd=lwd, lty=lty, ...,
                  style=c("isomeans", "confint", "both"),
                  type=c("mca", "lmat", "linfct", "none"))
# S3 method for glht
mmcplot(mmc, col=c("black","red"), lwd=c(1,1), lty=c(2,1),
                  focus=mmc$focus, ...)
# S3 method for mmc.multicomp
mmcplot(mmc, col=c("black","red"), lwd=c(1,1), lty=c(2,1), ...)
# S3 method for multicomp
mmcplot(mmc, col=col, lwd=lwd, lty=lty, ...)
# S3 method for default
mmcplot(mmc, ...)

Arguments

mmc

mmc object or other object as indicated by method.

col,lwd, lty

Standard xyplot arguments applied to the line segments representing the contrasts.

focus

Name of the factor for which the glht object was constructed.

Other arguments to be passed on to the functions called by the methods.

style

Style of graph: The default isomeans is the standard MMC plot with the isomeans grid. confint is a confidence interval plot, similar to the plot produced by multcomp:::plot.glht. both prints both the isomeans and the confint plot as two panels of a trellis structure. When the underlying sets of means are close to each other, there will of necessity be overprinting in the isomeans panel and the confint panel will be needed as a tiebreaker. By default the xlim for the confint style will match the xlim of the corresponding isomeans plot.

type

mca for the default paired-comparisons plot. lmat or linfct for a user-specified set of contrasts. none for confidence intervals on the set of group means (that is, no comparisons).

Value

A trellis object containing the graphs.

References

See mmc for the references.

See Also

mmc for the discussion of the MMC and for many examples. The functions mmcisomeans, mmcmatch, mmcboth are the internal functions that do the actual work of plotting.

Examples

Run this code
# NOT RUN {
data(catalystm)
catalystm1.aov <- aov(concent ~ catalyst, data=catalystm)
catalystm.mmc <-
   mmc(catalystm1.aov, linfct = mcp(catalyst = "Tukey"))
mmcplot(catalystm.mmc)
mmcplot(catalystm.mmc, style="both", MMCname="catalyst")
# }

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