library(ggtukey)
library(ggplot2)
library(palmerpenguins)
library(Hmisc)
#>
#> Attaching package: 'Hmisc'
#> The following objects are masked from 'package:base':
#>
#> format.pval, units
data(penguins)
geom_tukey
The package includes a geom (geom_tukey
) that can be
used to easily overlay compact
letter displays onto ggplot2 figures.
penguins |> tidyr::drop_na(sex, species) |>
ggplot(aes(x=species, y=body_mass_g)) +
geom_boxplot() +
geom_jitter(col="slategray", alpha=0.6) +
facet_wrap(~sex) +
geom_tukey(where="whisker") +
ylab("Body mass (g)") +
xlab("Species") + egg::theme_article()
The geom includes several arguments that can be modified to choose
the statistics that are done to generate the compact letter displays, as
well as adjusting their position on the plot. The test
argument determines what kind of statistical test is conducted, while
the type
argument controls whether statistics are done
two-wayly
(e.g. with a two-way ANOVA) or
one-wayly
(e.g. in separate one-way ANOVAs for each
faceting variable). There are also several arguments that can be used to
adjust the positioning of the letters, including where
to
choose the basic position of the labels. Finer adjustments can then be
made using the hjust
and vjust
arguments to
nudge the letters horizontally or vertically.
boxplot_letters
The package also includes a convenience function
boxplot_letters
for quickly creating boxplots with compact
letter displays using even simpler syntax.
boxplot_letters
also supported faceting using the
group
argument. For example, we might want to break our
penguin data down by sex:
Or look for sex differences within each of our three penguin species:
When there is a grouping variable, there are (at least) two possible
ways to run the statistics that may yield different results. By default
a two-way
test is conducted where TukeyHSD
is
run on a full ANOVA (aov)
with species and sex as an interaction, returning all pairwise
comparisons of these two factors. If the comparisons are independent,
type="one-way"
can be selected to run independent Tukey
tests within each group.
boxplot_letters(data=penguins, x=species, y=body_mass_g, group=sex, type="one-way", vjust=-0.5, hjust=-0.2)
Raw data can also be plotted in various ways using the
raw
argument to specify the desired geom for plotting raw
data: e.g. geom_point
(points
),
geom_dotplot
(dots
), geom_jitter
(jitter
).
To create a dynamite plot (which I do not advocate):
data(iris)
p<-ggplot(data = iris, aes(x=Species, y=Petal.Width)) +
geom_jitter(aes(color=Species, fill=Species), alpha=0.6, width=0.15) +
geom_point(aes(fill = Species), position = "identity", stat = "summary", fun = "mean") +
stat_summary(fun.data = mean_cl_normal, geom = "errorbar", width=0.3) +
geom_tukey(where="cl_normal") + guides(fill = "none")
p
Piepho, Hans-Peter. “An Algorithm for a Letter-Based Representation of All-Pairwise Comparisons.” Journal of Computational and Graphical Statistics 13, no. 2 (June 1, 2004): 456–66. https://doi.org/10.1198/1061860043515.
Piepho, Hans-Peter. “Letters in Mean Comparisons: What They Do and Don’t Mean.” Agronomy Journal 110, no. 2 (2018): 431–34. https://doi.org/10.2134/agronj2017.10.0580.
Graves S, Piepho H, Dorai-Raj LSwhfS (2019). multcompView: Visualizations of Paired Comparisons. R package version 0.1-8, (https://CRAN.R-project.org/package=multcompView)..)