感谢您使用最小可重复示例更新您的问题。一个潜在的“简单”解决方案是将均值添加到现有图中：

library(tidyverse)
library(ggdist)

iris %>%
  ggplot(aes(x=Petal.Length, y=Species))+
  stat_slab(aes(fill=Species), scale = 0.7) +
  stat_dotsinterval(aes(fill=Species),
                    side = "bottom",
                    scale = 0.7,
                    slab_size = NA) + 
  scale_fill_brewer(palette = "Set1") +
  stat_summary(aes(color = "mean"), 
               fun=mean, geom="point", shape="|", size=5) +
  theme_bw(base_size = 16) +
  theme(legend.position = "top")+
# scale_x_continuous(limits = c(-4.5, .5), breaks = seq(-4.5, 0.5, by = 0.5))+
  labs(title="Raincloud plot with ggdist") +
  scale_color_manual(name = "",
                     values = c("mean" = "cyan"))

创建于2023年3月2日，使用reprex v2.0.2
如果这不合适，我想你需要自己计算统计数据。

library(tidyverse)
library(ggdist)
iris %>%
  group_by(Species) %>%
  mutate(mean = mean(Petal.Length),
         se = sd(Petal.Length)/sqrt(length(Petal.Length))) %>%
  ungroup() %>%
  ggplot(aes(x=Petal.Length, y=Species)) +
  stat_slab(aes(fill = Species)) +
  stat_dots(side = "bottom", shape = 16) + 
  scale_fill_brewer(palette = "Set1") +
  geom_errorbar(aes(xmin = mean - 1.96 * se,
                    xmax = mean + 1.96 * se), width = 0.2) +
  stat_summary(fun=mean, geom="point", shape=16, size=2.5) +
  theme_bw(base_size = 16) +
  theme(legend.position = "top")+
  # scale_x_continuous(limits = c(-4.5, .5), breaks = seq(-4.5, 0.5, by = 0.5))+
  labs(title="Raincloud plot with ggdist")

创建于2023-03-07带有reprex v2.0.2