stat_compare_means() 用于多面 ggplot 数据中的多个组

Question

您好，我有一个示例 df 如下，我正在尝试使用ggpubr带有该stat_compare_means()函数的包执行 t 测试，但是我无法让它在我想要的组之间进行比较：

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)

从图中可以看出，它只有一个“ns”用于统计测试，但是否有可能在所有三个比较中都使用它？我希望测试在 A、B 和 C 的分组变量之间进行，例如在“四”的 3 个箱线图中，将有 3 个 A 与 B、A 与 C 和 B 与 C 的比较。我也尝试添加comparisons = list(c("A","B"),c("A","C"),c("B","C"))作为comparisons参数，但它也不起作用。多谢！

Answer 1

编辑

这里的关键是比较基于：

比较：长度为 2 的向量列表。向量中的条目要么是 x 轴上 2 个值的名称，要么是与要比较的感兴趣组的索引相对应的 2 个整数。

因此，您必须interaction在 x 轴上使用才能比较每个分组的箱线图。这是一个可重现的示例：

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()

^{创建于 2022-08-31，使用reprex v2.0.2}

旧答案

也许你想要这样的东西。另请确保删除limits中的scale_y_continuous，否则标签将不会显示。这是一个可重现的示例：

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.

^{创建于 2022-08-28，使用reprex v2.0.2}