plot.mmc.multicomp: MMC (Mean-mean Multiple Comparisons) plot.

In HH: Statistical Analysis and Data Display: Heiberger and Holland

MMC (Mean–mean Multiple Comparisons) plot.

Description

MMC (Mean–mean Multiple Comparisons) plot. The plot method documented here is no longer recommended for R; use mmcplot instead. This method is still necessary for S-Plus.

Usage

## S3 method for class 'mmc.multicomp'
plot(x,
     xlab="contrast value",
     ylab=none$ylabel,
     focus=none$focus,
     main= main.method.phrase,
     main2=main2.method.phrase,
     main.method.phrase=
       paste("multiple comparisons of means of", ylab),
     main2.method.phrase=paste("simultaneous ",
       100*(1-none$alpha),"% confidence limits, ",
       method, " method", sep="" ),
     ry.mmc=TRUE,
     key.x=par()$usr[1]+ diff(par()$usr[1:2])/20,
     key.y=par()$usr[3]+ diff(par()$usr[3:4])/3,
     method=if (is.null(mca)) lmat$method else mca$method,
     print.lmat=(!is.null(lmat)),
     print.mca=(!is.null(mca) && (!print.lmat)),
     iso.name=TRUE,
     x.offset=0,
     col.mca.signif="red",  col.mca.not.signif="black",
     lty.mca.signif=1,  lty.mca.not.signif=6,
     lwd.mca.signif=1,  lwd.mca.not.signif=1,
     col.lmat.signif="blue", col.lmat.not.signif="black",
     lty.lmat.signif=1, lty.lmat.not.signif=6,
     lwd.lmat.signif=1, lwd.lmat.not.signif=1,
     lty.iso=7, col.iso="darkgray", lwd.iso=1,
     lty.contr0=2, col.contr0="darkgray", lwd.contr0=1,
     decdigits.ybar=2,
     ...
     )

Arguments

x	mmc.multicomp object
xlab	"contrast value". An alternate "" can help unclutter a figure when several MMC plots are displayed together.
ylab	name of response variable
focus	define the factor to compute contrasts of.
main, main2	main and second line of title of plot
main.method.phrase, main2.method.phrase	default expressions for title of plot
ry.mmc	range of values on the y-axis. It is similar to par("ylim"), but not the same as additional calculations are needed to maintain the isomeans grid as a square.
key.x, key.y	location of the key displayed when iso.name=FALSE.
method	method used to construct contrasts and confidence intervals. See the type argument to glht for the list.
print.lmat	logical. If TRUE, then display the user-specified contrasts.
print.mca	logical. If TRUE, then display the pair-wise contrasts.
iso.name	logical. If TRUE, label the isomeans grid with the factor levels. If FALSE, label the isomeans grid with sequential numbers and display a key relating the numbers to the factor levels.
x.offset	amount to move the vertical 0 line to the left or right to reduce overprinting of labels and plotted lines.
col.mca.signif, lty.mca.signif, lwd.mca.signif	color, line type, line width for significant pairwise contrasts.
col.mca.not.signif, lty.mca.not.signif, lwd.mca.not.signif	color, line type, line width for non-significant pairwise contrasts.
col.lmat.signif, lty.lmat.signif, lwd.lmat.signif	color, line type, line width for significant user-specified contrasts.
col.lmat.not.signif, lty.lmat.not.signif, lwd.lmat.not.signif	color, line type, line width for non-significant user-specified contrasts.
lty.iso, col.iso, lwd.iso	color, line type, line width for the isomeans grid.
lty.contr0, col.contr0, lwd.contr0	color, line type, line width for the vertical contrast=0 line.
decdigits.ybar	number of decimal digits in the left-axis labels.
...	other arguments, currently ignored.

Note

plot.mmc.multicomp chooses sensible defaults for its many arguments. They will often need manual adjustment. The examples show several types of adjustments. We have changed the centering and scaling to avoid overprinting of label information. By default the significant contrasts are shown in a more intense color than the nonsignificant contrasts. We have an option to reduce the color intensity of the isomeans grid.

When there is overprinting of labels (a consequence of level means being close together), a tiebreaker plot may be needed. See ?MMC for an example.

Author(s)

Richard M. Heiberger <[e-mail]>

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://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.

Hsu, J. and Peruggia, M. (1994). "Graphical representations of Tukey's multiple comparison method." Journal of Computational and Graphical Statistics, 3:143–161.

See Also

mmc, plotMatchMMC, mmcplot.

Examples

data(catalystm)
catalystm1.aov <- aov(concent ~ catalyst, data=catalystm)
summary(catalystm1.aov)

## See ?MMC to see why these contrasts are chosen
catalystm.lmat <- cbind("AB-D" =c( 1, 1, 0,-2),
                        "A-B"  =c( 1,-1, 0, 0),
                        "ABD-C"=c( 1, 1,-3, 1))
dimnames(catalystm.lmat)[[1]] <- levels(catalystm$catalyst)


catalystm.mmc <-
if.R(r={mmc(catalystm1.aov, linfct = mcp(catalyst = "Tukey"),
            focus.lmat=catalystm.lmat)}
    ,s={multicomp.mmc(catalystm1.aov, focus.lmat=catalystm.lmat,
                     plot=FALSE)}
)

## Not run: 
## pairwise contrasts, default settings
plot(catalystm.mmc, print.lmat=FALSE)

## End(Not run)

## Centering, scaling, emphasize significant contrasts.
## Needed in R with 7in x 7in default plot window.
## Not needed in S-Plus with 4x3 aspect ratio of plot window.
plot(catalystm.mmc, x.offset=2.1, ry.mmc=c(50,58), print.lmat=FALSE)

## user-specified contrasts
plot(catalystm.mmc, x.offset=2.1, ry.mmc=c(50,58))

## reduce intensity of isomeans grid, number isomeans grid lines
plot(catalystm.mmc, x.offset=2.1, ry.mmc=c(50,58),
     lty.iso=2, col.iso='darkgray', iso.name=FALSE)

## both pairwise contrasts and user-specified contrasts
plot(catalystm.mmc, x.offset=2.1, ry.mmc=c(50,58), lty.iso=2,
     col.iso='darkgray', print.mca=TRUE)

## Not run: 
## newer mmcplot
mmcplot(catalystm.mmc)
mmcplot(catalystm.mmc, type="lmat")

## End(Not run)

HH documentation built on Aug. 9, 2022, 5:08 p.m.