CJ Mayes recently posted some really nice plots for visualizing group differences to Twitter.
My personal favorite was the bottom right plot, which can be a nice way of visualizing pre and post changes in a study. I believe the original plots were done in Tableau, so I’ve gone ahead and reproduced that bottom right plot in R.
You can grab the full code, all in one piece, from my GitHub page.
Simulate Some Data
library(tidyverse)
library(gghalves)
theme_set(theme_light())
set.seed(1234)
dat <- tibble( subject = LETTERS[1:26], pre = rnorm(n = 26, mean = 10, sd = 3) ) %>%
mutate(post = pre + rnorm(n = 26, mean = 0, sd = 2))
dat_long <- dat %>%
pivot_longer(cols = -subject) %>%
mutate(name = factor(name, levels = c("pre", "post")))
Create the plot
dat_long %>%
ggplot(aes(x = name, y = value)) +
geom_line(aes(group = subject),
color = "light grey",
size = 0.7) +
geom_point(aes(group = subject,
color = name),
alpha = 0.7,
size = 2) +
geom_half_violin(aes(x = name),
data = dat_long %>% filter(name == 'pre'),
fill = "light grey",
color = "light grey",
side = 'l',
alpha = 0.7) +
geom_half_violin(aes(x = name),
data = dat_long %>% filter(name == 'post'),
fill = "palegreen",
color = "palegreen",
side = 'r',
alpha = 0.7) +
scale_color_manual(values = c("pre" = "light grey", "post" = "palegreen")) +
labs(x = "Test Time",
y = NULL,
title = "Changes from Pre to Post") +
theme(axis.text = element_text(face = "bold", size = 12),
axis.title = element_text(face = "bold", size = 15),
plot.title = element_text(size = 18),
legend.position = "none")
