plot.multicomp: Multiple comparisons plot that gives independent user control...

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

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

Description

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 R, plot.multicomp.adjusted replaces the bounds calculated by multcomp:::confint.glht with bounds based on a common standard error for a set of anova tables that are partitioned for the simple effects on an analysis conditioned on the levels of one of the factors. In S-Plus, plot.multicomp.hh augments the standard plot.multicomp to give additional user arguments to control the appearance of the plot.

plotMatchMMC uses the plot.multicomp.hh code. plotMatchMMC must immediately follow a plot of an mmc.multicomp object and is applied to either the $mca or $lmat component of the mmc.multicomp object. plotMatchMMC is used as a tiebreaker plot for the MMC plot. plotMatchMMC matches the horizontal scaling of the MMC plot and displays the individual contrasts in the same order as the MMC plot. See mmc for examples.

These functions are no longer recommended. Use mmcplot instead.

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, ylabel.inside=FALSE)

plotMatchMMC(x, ...,
             xlabel.print=FALSE,
             cex.axis=par()$cex.axis,
             col.signif='red', main="",
             ylabel.inside=FALSE,
             y.axis.side=4,
             adjusted=FALSE)

Arguments

x	A "multicomp" object. plotMatchMMC will also accept a mmc.multicomp object. It will use the lmat component if there is one, otherwise it will use the mca component.
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.
ylabel.inside	Logical value, if FALSE (the default), the plotMatchMMC right-axis labels are in the margin. If TRUE, the right-axis labels are in the figure area. Setting the argument to TRUE makes sense when plotting the lmat component of an mmc.multicomp object.
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 to make better use of the space on the plot. S-Plus only.
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 plotMatchMMC.
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 a tiebreaker plot for the MMC plot. S-Plus only.
cex.axis	cex for axis ticklabels.
main	Main title for plot.
adjusted	Logical. When TRUE, HH:::plot.multicomp.adjusted is used to replace the standard confidence bounds calculated by multcomp:::confint.glht, with bounds calculated by as.multicomp.glht with a rescaled critical value based on rescaling the standard error. This rescaling is used to construct a common standard error for a set of anova tables that are partitioned for the simple effects on an analysis conditioned on the levels of one of the factors. See the clover.commonstrMS.clov.mmc example in file hh("scripts/Ch12-tway.r").

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 a "glht" object and plots that with the appropriate plot method.

Note

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

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, 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.

Examples

## data and ANOVA
data(catalystm)

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.

HH documentation built on May 29, 2024, 6:24 a.m.