HH (version 2.2-17)

plot.multicomp: 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 S-Plus, plot.multicomp.hh augments the standard plot.multicomp to give additional user arguments to control the appearance of the plot. plot.matchMMC uses the plot.multicomp.hh code. plot.matchMMC 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. plot.matchMMC is used as a tiebreaker plot for the MMC plot. plot.matchMMC 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.

Usage

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

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.

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,#ifndef S-Plus glht. #endif #ifdef S-Plus multicomp. #endif

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.