How to plot additional statistics in boxplot for each group?
plot, r
Solution
Here's one way using `ggplot2`. First we can compute the p-values separately for every month/country combination (I use `data.table`. you can use whichever way you're comfortable with). Then, we add `geom_text` and specify `pvalue` as the label and specify x and y coordinates where the text should be within each facet.
require(data.table)
dt <- data.table(df)
pval <- dt[, list(pvalue = paste0("pval = ", sprintf("%.3f",
summary(aov(x ~ type))[[1]][["Pr(>F)"]][1]))),
by=list(country, month)]
ggplot(data = df, aes(x=type, y=x)) + geom_boxplot() +
geom_text(data = pval, aes(label=pvalue, x="river", y=2.5)) +
facet_grid(country ~ month) + theme_bw() +
theme(panel.margin=grid::unit(0,"lines"), # thanks to @DieterMenne
strip.background = element_rect(fill = NA),
panel.grid.major = element_line(colour=NA),
panel.grid.minor = element_line(colour=NA))
Problem
I would like to see boxplots of combination of factors and I was told to use lattice for that. I tried it and it looks like this: But now I would like to also add an ANOVA statistics to each of the groups. Possibly the statistics should display the p-value in each panel (in the white below the e.g. "Australia"). How to do this in lattice? Note that I don't insist on lattice at all... Example code: ``` set.seed(123) n <- 300 country <- sample(c("Europe", "Africa", "Asia", "Australia"), n, replace = TRUE) type <- sample(c("city", "river", "village"), n, replace = TRUE) month <- sample(c("may", "june", "july"), n, replace = TRUE) x <- rnorm(n) df <- data.frame(x, country, type, month) bwplot(x ~ type|country+month, data = df, panel=function(...) { panel.abline(h=0, col="green") panel.bwplot(...) }) ``` The code to perform ANOVA for one of the groups and to extract p-value is this: ``` model <- aov(x ~ type, data = df[df$country == 'Africa' & df$month == 'may',]) p_value <- summary(model)[[1]][["Pr(>F)"]][2] ```