If I have some data and do an ANOVA and post-hoc tests, how do I make a boxplot that adds the post-hoc classification automatically, rather than having to edit the figure outside of R?
For example, here are some data to get started:
install.packages("reshape", dependencies=T)
library(reshape)
x <- rnorm(30)
y <- rnorm(30)+1
z <- rnorm(30)+0.5
data.1 <- data.frame(x, y, z)
data.2 <- melt(data.1)
Here's code for running a simple one way ANOVA and all of the unplanned comparision post-hoc tests:
linear.model <- lm(value~variable, data=data.2)
anova(linear.model)
# Analysis of Variance Table
# Response: value
# Df Sum Sq Mean Sq F value Pr(>F)
# variable 2 10.942 5.4710 5.8628 0.004087 **
# Residuals 87 81.185 0.9332
TukeyHSD(aov(linear.model))
# Tukey multiple comparisons of means
# 95% family-wise confidence level
# Fit: aov(formula = linear.model)
# $variable
# diff lwr upr p adj
# y-x 0.8344105 0.2396705 1.42915051 0.0034468
# z-x 0.2593612 -0.3353788 0.85410126 0.5539050
# z-y -0.5750493 -1.1697893 0.01969078 0.0602975
At this point, I want to classify x in group "a", y in group "b" and z in group "a,b". I can make a boxplot, but how do you annotate it with the letters?
boxplot(value~variable, data=data.2)
If you don't mind using the ggplot2 package, here's how I would make the figure:
First, add a column to your data frame (data.2) with the text labels:
Install and load the ggplot2 package:
To understand the code for the figure, I'll build it in steps. First just plot the means for each of the three groups:
Next, add the text labels:
Finally, add the boxplot geom and clean it up a little: