Comments (5)
@IsabelPotani You can have a look at ggstatsplot, which uses ggsignif to show pairwise comparisons with statistics adjusted for multiple comparisons.
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Thanks, both. Your solutions have helped to resolve my problem
from ggsignif.
Hi Isabel,
unfortunately, the Bonferroni (or other multiple testing corrections) are not supported by ggsignif
. You will have to calculate the tests manually, calculate the correction, and then provide the annotation to ggsignif
. Please see the 'Advanced Example' on how to do this.
Best,
Constantin
from ggsignif.
@IsabelPotani You can have a look at ggstatsplot, which uses ggsignif to show pairwise comparisons with statistics adjusted for multiple comparisons.
Hi. Thanks for your help last time. I am trying to change the annotation for pairwise comparisons to asterisk and not the actual p values using the code below, but it's not working. Can you help me pick out what I am doing wrong?
ggbetweenstats(
data = survival1b,type="p",results.subtitle="FALSE",k=2,
x=site, y = hos_stay3, outlier.tagging = FALSE,pairwise.display="significant", plot.type = "box",pairwise.annotation = "asterisk", p.adjust.method="bonferroni", xlab="Site",ylab="Number of days hospitalised" ,title = "Duration of hospital stay", )+ggplot2::scale_y_continuous( breaks = seq(from = 0, to = 43, by = 2))
from ggsignif.
Here is an example:
library(ggplot2)
library(ggsignif)
library(dplyr, warn.conflicts = FALSE)
library(ggstatsplot)
# creating a basic plot
p <- ggplot(iris, aes(Species, Sepal.Width)) +
geom_boxplot()
# using `pairwise_comparisons()` package to create a data frame with results
df <- pairwise_comparisons(iris, Species, Sepal.Width) %>%
dplyr::mutate(groups = purrr::pmap(.l = list(group1, group2), .f = c)) %>%
dplyr::arrange(group1)
# add new significance column based on standard APA guidelines
signif_column <- function(data, p) {
dplyr::mutate(
data,
significance = dplyr::case_when(
{{ p }} >= 0.050 ~ "ns",
{{ p }} < 0.050 & {{ p }} >= 0.010 ~ "*",
{{ p }} < 0.010 & {{ p }} >= 0.001 ~ "**",
{{ p }} < 0.001 ~ "***"
)
)
}
df <- signif_column(df, p.value)
# using `geom_signif` to display results
p +
ggsignif::geom_signif(
comparisons = df$groups,
map_signif_level = TRUE,
tip_length = 0.01,
y_position = c(4.75, 5.00, 5.25),
annotations = df$significance,
test = NULL,
na.rm = TRUE
)
Created on 2022-12-14 with reprex v2.0.2
from ggsignif.
Related Issues (20)
- Figure out where the `WARNING`s and `NOTE`s in `R CMD check` are coming from HOT 1
- Manual vertical brackets do not work: "arguments imply differing number of rows" HOT 1
- Warning message: Ignoring unknown aesthetics: xmin, xmax, annotations, y_position HOT 3
- adding scale_y_log10 changes y-axis to a weird range
- geom_signif does not plot comparison on the facetted plot with free x scale HOT 2
- Where can we find the significance level in the ggplot object slots? HOT 1
- Rename default branch from `master` to `main` HOT 3
- CRAN release 0.6.4 HOT 3
- Feature request - add more distance between comparisons and data HOT 4
- geom_signif - all comparisons dissappear when one comparison has missings HOT 2
- Significance stars are misaligned when using "NS" as well
- ggsignif results don't match with anova significance HOT 1
- Use cross symbol when p <.10?
- what are * , ** , *** correspond if specific values by user is not given? HOT 1
- How do I hide the no significant (NS) comparisons?
- Adding significance bar on coupled boxplots
- FDR warning HOT 1
- Show exact p value in comparisons HOT 3
- ggsignif facetting issue - Missing significance labels in certain facets
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