R：t.test 在 facet_grid 中（ggplot）

Question

这是一个非常具体的问题，但我已经拥有并使用了这个详细且运行良好的代码，所以我希望找到调整它所需的微小变化并使其适用于下一个复杂级别。我得到了什么：

library(ggplot2)
library(ggpubr)
head(ToothGrowth)
ToothGrowth$dose <- as.factor(ToothGrowth$dose)
# add a grouping ID for measured individuals:
ToothGrowth$ID <- rep(c(1:30),2)

# The code I am using now (basically a solution I got from my former question answered by Allan Cameron (user:12500315)):
ggplot(ToothGrowth, aes(supp, len, fill = dose, alpha = supp)) +
  geom_boxplot() +
  scale_fill_manual(name   = "Dosis", 
                    labels = c("0.5", "1", "2"), 
                    values = c("darkorange2", "olivedrab", "cadetblue4")) +
  scale_alpha_discrete(range = c(0.5, 1), 
                       guide = guide_none()) +
  geom_line(inherit.aes = FALSE, 
            aes(supp, len, group = ID), 
            color = "gray75") +
  geom_text(data = data.frame(
    x    = 1.5, 
    y    = 40, 
    dose = c("0.5", "1", "2"),
    pval = sapply(c("0.5", "1", "2"), function(x) {
      round(t.test(len ~ supp, 
                   data = ToothGrowth[ToothGrowth$dose == x,],
                   paired = TRUE)$p.val, 4)})), 
    inherit.aes = FALSE,
    aes(x = 1.5, y = 40, label = paste("T test: p value =", pval)), 
    check_overlap = TRUE) +
  facet_grid(~dose) +
  theme_classic() +
  theme(legend.position = "top",
        strip.background = element_rect(fill = "gray95", size = 0.25))

# Follow-up question:
# What I want to do next: having another facetting variable ('researcher')
ToothGrowth_1 <- ToothGrowth
# create a random numerical factor to multiply measures with and then enlarge the dataset by a second set of measurements from a different 'researcher':
r <- runif(60, min=0, max=3)
ToothGrowth_1$len <- ToothGrowth_1$len*r
ToothGrowth$researcher <- "A"
ToothGrowth_1$researcher <- "B"
ToothGrowth_total <- rbind(ToothGrowth, ToothGrowth_1)

现在，我想绘制与上面相同的图，但对两个 'researcher' 组（A 与 B）进行水平切面分割。我通过创建 'researcher' 和 'dose' 的交互项并将 facet_grid 替换为 facet_wrap 来找到解决方法，但我宁愿看到 [= 的解决方案20=]，因为它使其他一切从那里变得更容易。感谢您的帮助，非常感谢！

Answer 1

感谢您发布 follow-up。

执行此操作的自然方法是 map 两个级别，尽管我认为与其完全重写来完成此操作，我可能只需要连接 2 个 sapply 调用 - 一个用于新因素的每个级别：

ggplot(ToothGrowth_total, aes(supp, len, fill = dose, alpha = supp)) +
  geom_boxplot() +
  scale_fill_manual(name   = "Dosis", 
                    labels = c("0.5", "1", "2"), 
                    values = c("darkorange2", "olivedrab", "cadetblue4")) +
  scale_alpha_discrete(range = c(0.5, 1), 
                       guide = guide_none()) +
  geom_line(inherit.aes = FALSE, 
            aes(supp, len, group = ID), 
            color = "gray75") +
  geom_text(data = data.frame(
    x    = 1.5, 
    y    = c(40, 40, 40, 70, 70, 70), 
    researcher = c("A", "A", "A", "B", "B", "B"),
    dose = c("0.5", "1", "2", "0.5", "1", "2"),
    pval = c(sapply(c("0.5", "1", "2"), function(x) {
            round(t.test(len ~ supp, 
            data = subset(ToothGrowth_total, dose == x & researcher == "A"),
            paired = TRUE)$p.val, 4)}), 
            sapply(c("0.5", "1", "2"), function(x) {
            round(t.test(len ~ supp, 
            data = subset(ToothGrowth_total, dose == x & researcher == "B"),
            paired = TRUE)$p.val, 4)}))),
    inherit.aes = FALSE,
    aes(x = x, y = y, label = paste("T test: p value =", pval)), 
    check_overlap = TRUE) +
  facet_grid(researcher~dose, scales = "free_y") +
  theme_classic() +
  theme(legend.position = "top",
        strip.background = element_rect(fill = "gray95", size = 0.25))

Answer 2

其实我找到了一个更简单的方法，如果我没记错的话：

ToothGrowth_total$researcher_dose <- interaction(ToothGrowth_total$researcher, ToothGrowth_total$dose)

ggplot(ToothGrowth_total, aes(supp, len, fill = dose, alpha = supp)) +
  geom_boxplot() +
  scale_fill_manual(name   = "Dosis", 
                    labels = c("0.5", "1", "2"), 
                    values = c("darkorange2", "olivedrab", "cadetblue4")) +
  scale_alpha_discrete(range = c(0.5, 1), 
                       guide = guide_none()) +
  geom_line(inherit.aes = FALSE, 
            aes(supp, len, group = ID), 
            color = "gray75") +
  # geom_text(data = data.frame(
  #   x    = 1.5, 
  #   y    = c(40, 40, 40, 70, 70, 70), 
  #   researcher = c("A", "A", "A", "B", "B", "B"),
  #   dose = c("0.5", "1", "2", "0.5", "1", "2"),
  #   pval = c(sapply(c("0.5", "1", "2"), function(x) {
  #     round(t.test(len ~ supp, 
  #                  data = subset(ToothGrowth_total, dose == x & researcher == "A"),
  #                  paired = TRUE)$p.val, 4)}), 
  #     sapply(c("0.5", "1", "2"), function(x) {
  #       round(t.test(len ~ supp, 
  #                    data = subset(ToothGrowth_total, dose == x & researcher == "B"),
  #                    paired = TRUE)$p.val, 4)}))),
  #   inherit.aes = FALSE,
  #   aes(x = x, y = y, label = paste("T test: p value =", pval)), 
  #   check_overlap = TRUE) +
# => instead subsituted by: 
  stat_compare_means(aes(x="researcher_dose"), method = "t.test", paired = TRUE)+ 
  facet_grid(researcher~dose, scales = "free_y") +
  theme_classic() +
  theme(legend.position = "top",
        strip.background = element_rect(fill = "gray95", size = 0.25))

我希望我没有遗漏任何重要信息，但它会产生相同的 t.test 结果，因此我认为它是正确的。如果没有，请告诉我！唯一的区别是 'researcher_dose' 现在也显示为 x 轴标签。

R：t.test 在 facet_grid 中（ggplot）

R: t.test in a facet_grid (ggplot)

r

ggplot2

t-test