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mmcplot

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

Description

MMC (Mean–mean Multiple Comparisons) plots in lattice

Usage

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

Author(s)

Richard M. Heiberger <rmh@temple.edu>

References

See mmc for the references.

Examples

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")

HH

Statistical Analysis and Data Display: Heiberger and Holland

v3.1-43

GPL (>= 2)

Authors

Richard M. Heiberger

Initial release

2020-11-27