CODEWITHSUNDEEP
rggplot2ggpubr
Jeff238
Jeff238

Reputation: 428

stat_compare_means() for multiple groups in faceted ggplot data

Hi I have a sample df as follows and I'm trying to perform t tests using the ggpubr package with the stat_compare_means() function however I cannot get it to compare across the groups that I want:

set.seed(13)
df = data.frame(grouping = c(rep("A",24),rep("B",24),rep("C",24)),
                id = c(rep(1,12),rep(2,12),rep(3,12),rep(4,12),rep(5,12),rep(6,12)),
                subject = c(rep(c("One","Two","Three","Four"),72)),
                family = c(rep(c("Red","Red","Red","Red","Blue","Blue","Blue","Blue","Green","Green","Green","Green"),6)),
                percent = sample(1:100,288,replace=T),
                result = "Good")

df %>%
    ggplot(aes(x=subject,y=percent,group = interaction(subject,grouping))) + 
    geom_boxplot(outlier.shape = NA) + 
    geom_point(aes(color = grouping),size=1.75,position = position_dodge(width = 0.75))+
    scale_y_continuous(breaks = seq(0, 100, by = 25),limits = c(0,103)) + 
    facet_grid(result~family,switch = "y") + 
    scale_x_discrete("") +
    theme_minimal() +
    stat_compare_means(aes(group = grouping),label="p.signif",
                       method = "t.test",paired=F,
                       tip.length=0,step.increase = 0.05)

As seen from the picture it only has one "ns" for the statistical test but is it possible to have it for all three comparisons? I would want the tests to be between the grouping variable of A, B, and C so for example within the 3 boxplots of "Four" there would be 3 comparisons for A vs B, A vs C, and B vs C. I also tried adding comparisons = list(c("A","B"),c("A","C"),c("B","C")) as the comparisons argument but it also didn't work. Thanks a lot!

enter image description here

Upvotes: 4

Views: 3305

Answers (1)

Quinten
Quinten

Reputation: 41225

Edit

The key thing here is that the comparisons are based on:

comparisons: A list of length-2 vectors. The entries in the vector are either the names of 2 values on the x-axis or the 2 integers that correspond to the index of the groups of interest, to be compared.

So you have to use interaction on the x-axis to be able to compare the boxplots per grouping. Here is a reproducible example:

library(ggplot2)
library(ggpubr)
library(dplyr)
df %>%
  ggplot(aes(x=interaction(subject, grouping),y=percent)) + 
  geom_boxplot(aes(group = interaction(subject, grouping)), outlier.shape = NA) + 
  geom_point(aes(color = grouping, group = grouping),size=1.75,position = position_dodge(width = 0.75))+
  scale_y_continuous(breaks = seq(0, 100, by = 25)) +
  scale_x_discrete("", limits = c("Four.A", "Four.B", "Four.C", "One.A", "One.B", "One.C", "Three.A", "Three.B", "Three.C", "Two.A", "Two.B", "Two.C"),
                   labels = c(rep(c("", "Four", "", "", "One", "", "", "Three", "", "", "Two", ""), 3))) +
  stat_compare_means(comparisons = list(c("Four.A","Four.B"),c("Four.A","Four.C"),c("Four.B","Four.C"), 
                                        c("One.A","One.B"),c("One.A","One.C"),c("One.B","One.C"),
                                        c("Three.A","Three.B"),c("Three.A","Three.C"),c("Three.B","Three.C"),
                                        c("Two.A","Two.B"),c("Two.A","Two.C"),c("Two.B","Two.C")),
                     method = "t.test",
                     paired=F,
                     tip.length=0,step.increase = 0.05) +
  facet_wrap(~ family) +
  theme_minimal()

Created on 2022-08-31 with reprex v2.0.2

Old answer

Maybe you want something like this. Also make sure to remove the limits in your scale_y_continuous, otherwise the labels won't be shown. Here is a reproducible example:

set.seed(13)
df = data.frame(grouping = c(rep("A",24),rep("B",24),rep("C",24)),
                id = c(rep(1,12),rep(2,12),rep(3,12),rep(4,12),rep(5,12),rep(6,12)),
                subject = c(rep(c("One","Two","Three","Four"),72)),
                family = c(rep(c("Red","Red","Red","Red","Blue","Blue","Blue","Blue","Green","Green","Green","Green"),6)),
                percent = sample(1:100,288,replace=T),
                result = "Good")

library(ggplot2)
library(ggpubr)
library(dplyr)
df %>%
  ggplot(aes(x=subject,y=percent, group = interaction(subject,grouping))) + 
  geom_boxplot(outlier.shape = NA) + 
  geom_point(aes(color = grouping, group = grouping),size=1.75,position = position_dodge(width = 0.75))+
  scale_y_continuous(breaks = seq(0, 100, by = 25)) + 
  facet_wrap(~ family) +
  scale_x_discrete("") +
  theme_minimal() +
  stat_compare_means(comparisons = list(c("Four", "One"), c("Four", "Three"), c("Four", "Two"), c("One", "Three"), c("One", "Two"), c("Three", "Two")),
                     aes(label=..p.adj..),
                     method = "t.test",paired=F,
                     tip.length=0,step.increase = 0.05)
#> Warning: Using `as.character()` on a quosure is deprecated as of rlang 0.3.0.
#> Please use `as_label()` or `as_name()` instead.
#> This warning is displayed once per session.

Created on 2022-08-28 with reprex v2.0.2

Upvotes: 5

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