How to visualize pairwise comparisons with `ggplot2`?

Question

Question

Is there a simple solution for visualizing pairwise comparisons and their p.values ​​(or just . , * , ** , *** ) on a box built with ggplot ?

An already built-in function (or something as convenient) would be great!

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Below is an example where you can work.

Dummy data

 require(ggplot2) set.seed(11) n=15 mu=1.2 d = data.frame(y=c(rnorm(n), rnorm(n), rnorm(n,mu), rnorm(n,mu)),x=rep(LETTERS[1:4],each=n)) 

Graph

 ggplot(d, aes(y=y, x=x)) + geom_boxplot() 

Statistical analysis

 m = aov(data=d, y~x) anova(m) # Analysis of Variance Table # Response: y # Df Sum Sq Mean Sq F value Pr(>F) # x 3 34.074 11.358 16.558 8.021e-08 *** # Residuals 56 38.414 0.686 TukeyHSD(m)$x diff lwr upr p adj BA 0.1989620 -0.6018277 0.9997517 9.123300e-01 CA 1.3858613 0.5850716 2.1866510 1.504711e-04 DA 1.7658291 0.9650394 2.5666188 1.639309e-06 CB 1.1868993 0.3861096 1.9876890 1.337608e-03 DB 1.5668671 0.7660774 2.3676568 1.824795e-05 DC 0.3799678 -0.4208219 1.1807575 5.941266e-01 

Answer 1

Here are a few options:

 # Add means and bootstrap confidence intervals to the boxplots ggplot(d, aes(y=y, x=x)) + geom_boxplot() + stat_summary(fun.data=mean_cl_boot, geom="errorbar", colour="red", width=0.1) + stat_summary(fun.y=mean, geom="point", colour="red") 

 # Anova m = aov(data=d, y~x) anova(m) tky = as.data.frame(TukeyHSD(m)$x) tky$pair = rownames(tky) # Plot pairwise TukeyHSD comparisons and color by significance level ggplot(tky, aes(colour=cut(`p adj`, c(0, 0.01, 0.05, 1), label=c("p<0.01","p<0.05","Non-Sig")))) + geom_hline(yintercept=0, lty="11", colour="grey30") + geom_errorbar(aes(pair, ymin=lwr, ymax=upr), width=0.2) + geom_point(aes(pair, diff)) + labs(colour="")