# plot.multicomp

##### 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

##### 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)*