library(ggpubr)
dat <- my_data
# Edit from here #
x <- which(names(dat) == "Species") # name of grouping variable
y <- which(names(dat) == "Sepal.Length" # names of variables to test
| names(dat) == "Sepal.Width"
| names(dat) == "Petal.Length"
| names(dat) == "Petal.Width")
method <- "t.test" # one of "wilcox.test" or "t.test"
paired <- FALSE # if paired make sure that in the dataframe you have first all individuals at T1, then all individuals again at T2
# Edit until here
# Edit at your own risk
for (i in y) {
for (j in x) {
ifelse(paired == TRUE,
p <- ggpaired(dat,
x = colnames(dat[j]), y = colnames(dat[i]),
color = colnames(dat[j]), line.color = "gray", line.size = 0.4,
palette = "npg",
legend = "none",
xlab = colnames(dat[j]),
ylab = colnames(dat[i]),
add = "jitter"
),
p <- ggboxplot(dat,
x = colnames(dat[j]), y = colnames(dat[i]),
color = colnames(dat[j]),
palette = "npg",
legend = "none",
add = "jitter"
)
)
# Add p-value
print(p + stat_compare_means(aes(label = paste0(..method.., ", p-value = ", ..p.format.., " (", ifelse(..p.adj.. >= 0.05, "not significant", ..p.signif..), ")")),
method = method,
paired = paired,
# group.by = NULL,
ref.group = NULL
))
}
}