# 1. Load required R packages
suppressPackageStartupMessages(library(ggpubr))
suppressPackageStartupMessages(library(rstatix))
# 2. Data preparation
df <- ToothGrowth
df$dose <- factor(df$dose)
# 3. Statistical tests
res.stats <- df %>%
group_by(dose) %>%
t_test(len ~ supp) %>%
adjust_pvalue() %>%
add_significance()
res.stats
## # A tibble: 3 x 11
## dose .y. group1 group2 n1 n2 statistic df p p.adj p.adj.signif
## <fct> <chr> <chr> <chr> <int> <int> <dbl> <dbl> <dbl> <dbl> <chr>
## 1 0.5 len OJ VC 10 10 3.17 15.0 0.00636 0.0127 *
## 2 1 len OJ VC 10 10 4.03 15.4 0.00104 0.00312 **
## 3 2 len OJ VC 10 10 -0.0461 14.0 0.964 0.964 ns
# 4. Create a stacked bar plot, add "mean_se" error bars
p <- ggbarplot(
df, x = "dose", y = "len", add = "mean_se",
color = "supp", palette = "jco"
)
# 5. Add p-values to the bar plot using ggpubr verbs
p + stat_pvalue_manual(
res.stats, x = "dose", y.position = c(30, 45, 60),
label = "p.adj.signif"
)
# or use ggplot2 verbs
p + geom_text(
aes(x = dose, y = c(25, 42, 60), label = p.adj.signif),
data = res.stats
)
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What if you had an additional level? Like you have dose but then you also have a group within dose? So, you have the doses repeated for Group A, Group B, and Group C, and you want the stacked bars for the dose as you have here but want that repeated for Group A, Group B, and Group C, and have them side by side so you would have 9 stacked bar plots with the error bars instead of 3. Thank you!