Raincloud plot with confidence

Question

I am trying to create a raincloud plot with a 95% confidence interval, however my code keeps on produces a raincloud plot with a boxplot interval. Meaning the black circle is the median not the mean. How can I change my code to add in error bars to achieve this?

Here are two codes I tried that create the raincloud plot, but no with the mean. I have attached how the plots look. The last image is how I want the plot to look. ")

Can be found here:
https://z3tt.github.io/Rainclouds/

ggplot(iris, aes(Species, Sepal.Width)) + ggdist::stat_halfeye(adjust = .5, width = .3, .width = c(0.5, 1)) + ggdist::stat_dots(side = "left", dotsize = .4, justification = 1.05, binwidth = .1)

Answer 1

Thanks for updating your question with a minimal reproducible example. One potential 'easy' solution is to add the mean to the existing plot:

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"))

^{Created on 2023-03-02 with reprex v2.0.2}

If this doesn't suit, I suspect you need to calculate the statistics yourself, e.g.

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")

^{Created on 2023-03-07 with reprex v2.0.2}