Barplot with significant differences and interactions?

Question

I would like to visualize my data and ANOVA statistics. It is common to do this using a barplot with added lines indicating significant differences and interactions. How do you make plot like this using R?

This is what I would like:

Significant differences:

Significant interactions:

Background

I am currently using barplot2{ggplots} to plot bars and confidence intervals, but I am willing to use any package/procedure to get the job done. To get the statistics I am currently using TukeyHSD{stats} or pairwise.t.test{stats} for differences and one of the anova functions (aov, ezANOVA{ez}, gls{nlme}) for interactions.

Just to give you an idea, this is my current plot:

Answer 1

As you are using function barplot2() from library gplots, will give example using this approach.

First, made barplot as given in help file of barplot2() function. ci.l and ci.u are fake confidence interval values. Barplot should be saved as object.

hh <- t(VADeaths)[1:2, 5:1]
mybarcol <- "gray20"
ci.l <- hh * 0.85
ci.u <- hh * 1.15
mp <- barplot2(hh, beside = TRUE,
               col = c("grey12", "grey82"),
               legend = colnames(VADeaths)[1:2], ylim = c(0, 100),
               cex.names = 1.5, plot.ci = TRUE, ci.l = ci.l, ci.u = ci.u)

If you look on object mp, it contains x coordinates for all bars.

 mp
     [,1] [,2] [,3] [,4] [,5]
[1,]  1.5  4.5  7.5 10.5 13.5
[2,]  2.5  5.5  8.5 11.5 14.5

Now I use upper confidence interval values to calculate coordinates for y values of segments. Segments will start at position that is 1 higher then the end of confidence intervals. y.cord contains four rows - first and second row correspond to first bar and other two rows to second bar. Highest y value is calculated from the maximal values of confidence intervals for each bar pair. x.cord values just repeat the same values which are in mp object, each 2 times.

y.cord<-rbind(c(ci.u[1,]+1),c(apply(ci.u,2,max)+5),
          c(apply(ci.u,2,max)+5),c(ci.u[2,]+1))
x.cord<-apply(mp,2,function(x) rep(x,each=2))

After barplot is made use sapply() to make five line segments (because this time there are 5 groups) using calculated coordinates.

sapply(1:5,function(x) lines(x.cord[,x],y.cord[,x]))

To plot texts above the segments calculate x and y coordinates, where x is middle point of two bar x values and y value is calculated from the maximal values of confidence intervals for each bar pair plus some constant. Then use function text() to add information.

x.text<-colMeans(mp)
y.text<-apply(ci.u,2,max)+7
text(c("*","**","***","NS","***"),x=x.text,y=y.text)