plot.mmc.multicomp

0th

Percentile

MMC (Mean--mean Multiple Comparisons) plot.

MMC (Mean--mean Multiple Comparisons) plot.

Keywords
hplot
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.

References

Heiberger, Richard~M. and Holland, Burt (2004b). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5. Heiberger, R.~M. and Holland, B. (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

Aliases
  • plot.mmc.multicomp
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)}
)

## pairwise contrasts, default settings
plot(catalystm.mmc, print.lmat=FALSE)

## 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)
Documentation reproduced from package HH, version 3.0-4, License: GPL (>= 2)

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