plot.multicomp

0th

Percentile

Multiple comparisons plot that gives independent user control over the appearance of the significant and not significant comparisons.

Multiple comparisons plot that gives independent user control over the appearance of the significant and not significant comparisons. In R, both plot.multicomp plot.multicomp.hh coerce their argument to an "glht" object and plots that with the appropriate plot method. In S-Plus, plot.multicomp.hh augments the standard plot.multicomp to give additional user arguments to control the appearance of the plot.

Keywords
dplot
Usage
## S3 method for class 'multicomp':
plot(x, ...) ## R only

## S3 method for class 'multicomp.hh': plot(x, ylabel = x$ylabel, href = 0, uniform = TRUE, plt.in = c(0.2, 0.9, 0.1, 0.9), x.label.adj=1, xrange.include=href, xlim, comparisons.per.page=21, col.signif=1, col.not.signif=1, lty.signif=4, lty.not.signif=4, lwd.signif=1, lwd.not.signif=1, ..., xlabel.print=TRUE, y.axis.side=2)

plot.matchMMC(x, ..., xlabel.print=FALSE, cex.axis=par()$cex.axis, col.signif='red', main="")

Arguments
x
A "multicomp" object.
ylabel
Y label on graph.
y.axis.side
Y labels are on the left by default when plotting a "multicomp" object. We move them to the right when matching the x-axis of an MMC plot.
...
other arguments to plot.multicomp.
href
reference line for the intervals. The default is 0. S-Plus only.
xrange.include
xlim will be extended to include these values. S-Plus only.
uniform
S-Plus only. Logical value, if TRUE and the plots fill more than one page, the scale will be uniform across pages.
plt.in
S-Plus only. Value for par("plt") to make better use of the space on the plotting page.
x.label.adj
S-Plus only. This is the par("adj") applied to the x-location of the y.labels on the multicomp plot.
xlim
x-range of the plot.
comparisons.per.page
The default S-Plus plot.multicomp hardwires this to 21, which allows for all pairwise comparisons of 7 levels taken 2 at a time. The HH plot.multicomp makes it a variable. Use it together with plt.in
lty.signif, lwd.signif
Line type, and line width for significant comparisons. S-Plus only.
col.signif
Color for significant comparisons. S-Plus only for plot.multicomp. Both R and S-Plus for plot.matchMMC.
col.not.signif, lty.not.signif, lwd.not.signif
Color, line type, and line width for non-significant comparisons. S-Plus only.
xlabel.print
logical. When TRUE, the caption under the plot is printed. When FALSE, the caption under the plot is not printed. It is helpful to set this to FALSE when the multicomp plot is used as
cex.axis
cex for axis ticklabels.
main
Main title for plot.
Value

  • plot.multicomp plots a "multicomp" object. In S-Plus, this masks the standard plot.multicomp in order to provide additional arguments for controlling the appearance. It defaults to the standard appearance. In R, it coerces its argument to an "glht" object and plots that with the appropriate plot method.

Note

The multiple comparisons calculations in R and S-Plus use completely different libraries. Multiple comparisons in R are based on glht. Multiple comparisons in S-Plus are based on multicomp. The MMC plot in the HH library is the same in both systems. The details of getting the plot differ.

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.

See Also

mmc in both languages, glht in R, multicomp in S-Plus.

Aliases
  • plot.multicomp
  • plot.multicomp.hh
  • plot.matchMMC
Examples
## data and ANOVA
catalystm <- read.table(hh("datasets/catalystm.dat"), header=FALSE,
                       col.names=c("catalyst","concent"))
catalystm$catalyst <- factor(catalystm$catalyst, labels=c("A","B","C","D"))

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

catalystm.mca <-
if.R(r=glht(catalystm1.aov, linfct = mcp(catalyst = "Tukey")),
     s=multicomp(catalystm1.aov, plot=FALSE))
if.R(s=plot(catalystm.mca),
     r=plot(confint(catalystm.mca, calpha=qtukey(.95, 4, 12)/sqrt(2))))
       ## calpha is strongly recommended in R with a large number of levels
       ## See ?MMC for details.
Documentation reproduced from package HH, version 2.1-23, License: GPL (>= 2)

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