Extension of 'ggplot2', 'ggstatsplot' creates
graphics with details from statistical tests included in the plots
themselves. It provides an easier API to generate information-rich plots
for statistical analysis of continuous (violin plots, scatterplots,
histograms, dot plots, dot-and-whisker plots) or categorical (pie and
bar charts) data. Currently, it supports only the most common types of
statistical tests: parametric, nonparametric, robust, and Bayesian
versions of t-test/ANOVA, correlation analyses, contingency table
analysis, meta-analysis, and regression analyses.
broomExtra, cowplot, dplyr, effectsize, ggcorrplot, ggExtra,
ggplot2, ggrepel, ggsignif, insight, ipmisc (>= 4.0.0),
pairwiseComparisons (>= 3.0.0), paletteer, parameters, purrr,
rlang, stats, statsExpressions (>= 0.5.1), tidyr

person(given = "Indrajeet",
family = "Patil",
role = c("cre", "aut", "cph"),
email = "patilindrajeet.science@gmail.com",
comment = c(ORCID = "0000-0003-1995-6531", Twitter = "@patilindrajeets"))
broomExtra (>= 4.1.0), cowplot, dplyr, effectsize (>= 0.4.0),
ggcorrplot, ggExtra, ggplot2, ggrepel, ggsignif, insight (>=
0.10.0), ipmisc (>= 4.1.0), pairwiseComparisons (>= 3.1.0),
paletteer, parameters (>= 0.9.0), purrr, rlang, stats,
statsExpressions (>= 0.6.0), tidyr
Indrajeet Patil [cre, aut, cph]
(<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)

cowplot, dplyr, ggcorrplot, ggExtra, ggplot2, ggrepel,
ggsignif, insight (>= 0.11.0), ipmisc, pairwiseComparisons,
paletteer, parameters (>= 0.10.0), performance (>= 0.6.0),
purrr, rlang, stats, statsExpressions (>= 0.6.1), tidyr, utils

Extension of 'ggplot2', 'ggstatsplot' creates
graphics with details from statistical tests included in the plots
themselves. It provides an easier API to generate information-rich plots
for statistical analysis of continuous (violin plots, scatterplots,
histograms, dot plots, dot-and-whisker plots) or categorical (pie and
bar charts) data. Currently, it supports the most common types of
statistical tests: parametric, nonparametric, robust, and Bayesian
versions of t-test/ANOVA, correlation analyses, contingency table
analysis, meta-analysis, and regression analyses.
cowplot, dplyr, ggcorrplot, ggExtra, ggplot2, ggrepel (>=
0.9.0), ggsignif, insight (>= 0.12.0), ipmisc (>= 5.0.2),
pairwiseComparisons (>= 3.1.2), paletteer, parameters (>=
0.11.0), performance, purrr, rlang, stats, statsExpressions (>=
0.7.0), tidyr, utils