Rename k parameter to digits and crosstabs defaults to two-sided alternative hypothesis

API

@@ -6,15 +6,15 @@ combine_plots(plotlist, plotgrid.args = list(), annotation.args = list(), guides
 extract_caption(p)
 extract_stats(p, ...)
 extract_subtitle(p)
-ggbarstats(data, x, y, counts = NULL, type = "parametric", paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(alpha = 1, fill = "white"), sample.size.label.args = list(size = 4), k = 2L, proportion.test = results.subtitle, perc.k = 0L, bf.message = TRUE, ratio = NULL, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, xlab = NULL, ylab = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
-ggbetweenstats(data, x, y, type = "parametric", pairwise.display = "significant", p.adjust.method = "holm", effsize.type = "unbiased", bf.prior = 0.707, bf.message = TRUE, results.subtitle = TRUE, xlab = NULL, ylab = NULL, caption = NULL, title = NULL, subtitle = NULL, k = 2L, var.equal = FALSE, conf.level = 0.95, nboot = 100L, tr = 0.2, centrality.plotting = TRUE, centrality.type = type, centrality.point.args = list(size = 5, color = "darkred"), centrality.label.args = list(size = 3, nudge_x = 0.4, segment.linetype = 4, min.segment.length = 0), point.args = list(position = ggplot2::position_jitterdodge(dodge.width = 0.6), alpha = 0.4, size = 3, stroke = 0, na.rm = TRUE), boxplot.args = list(width = 0.3, alpha = 0.2, na.rm = TRUE), violin.args = list(width = 0.5, alpha = 0.2, na.rm = TRUE), ggsignif.args = list(textsize = 3, tip_length = 0.01, na.rm = TRUE), ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
-ggcoefstats(x, statistic = NULL, conf.int = TRUE, conf.level = 0.95, k = 2L, exclude.intercept = FALSE, effectsize.type = "eta", meta.analytic.effect = FALSE, meta.type = "parametric", bf.message = TRUE, sort = "none", xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, only.significant = FALSE, point.args = list(size = 3, color = "blue", na.rm = TRUE), errorbar.args = list(height = 0, na.rm = TRUE), vline = TRUE, vline.args = list(linewidth = 1, linetype = "dashed"), stats.labels = TRUE, stats.label.color = NULL, stats.label.args = list(size = 3, direction = "y", min.segment.length = 0, na.rm = TRUE), package = "RColorBrewer", palette = "Dark2", ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
-ggcorrmat(data, cor.vars = NULL, cor.vars.names = NULL, matrix.type = "upper", type = "parametric", tr = 0.2, partial = FALSE, k = 2L, sig.level = 0.05, conf.level = 0.95, bf.prior = 0.707, p.adjust.method = "holm", pch = "cross", ggcorrplot.args = list(method = "square", outline.color = "black", pch.cex = 14), package = "RColorBrewer", palette = "Dark2", colors = c("#E69F00", "white", "#009E73"), ggtheme = ggstatsplot::theme_ggstatsplot(), ggplot.component = NULL, title = NULL, subtitle = NULL, caption = NULL, ...)
-ggdotplotstats(data, x, y, xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, k = 2L, results.subtitle = TRUE, point.args = list(color = "black", size = 3, shape = 16), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), ggplot.component = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
-gghistostats(data, x, binwidth = NULL, xlab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, k = 2L, ggtheme = ggstatsplot::theme_ggstatsplot(), results.subtitle = TRUE, bin.args = list(color = "black", fill = "grey50", alpha = 0.7), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), normal.curve = FALSE, normal.curve.args = list(linewidth = 2), ggplot.component = NULL, ...)
-ggpiestats(data, x, y = NULL, counts = NULL, type = "parametric", paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(direction = "both"), label.repel = FALSE, k = 2L, proportion.test = results.subtitle, perc.k = 0L, bf.message = TRUE, ratio = NULL, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
-ggscatterstats(data, x, y, type = "parametric", conf.level = 0.95, bf.prior = 0.707, bf.message = TRUE, tr = 0.2, k = 2L, results.subtitle = TRUE, label.var = NULL, label.expression = NULL, marginal = TRUE, point.args = list(size = 3, alpha = 0.4, stroke = 0), point.width.jitter = 0, point.height.jitter = 0, point.label.args = list(size = 3, max.overlaps = 1e+06), smooth.line.args = list(linewidth = 1.5, color = "blue", method = "lm", formula = y ~ x), xsidehistogram.args = list(fill = "#009E73", color = "black", na.rm = TRUE), ysidehistogram.args = list(fill = "#D55E00", color = "black", na.rm = TRUE), xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), ggplot.component = NULL, ...)
-ggwithinstats(data, x, y, type = "parametric", pairwise.display = "significant", p.adjust.method = "holm", effsize.type = "unbiased", bf.prior = 0.707, bf.message = TRUE, results.subtitle = TRUE, xlab = NULL, ylab = NULL, caption = NULL, title = NULL, subtitle = NULL, k = 2L, conf.level = 0.95, nboot = 100L, tr = 0.2, centrality.plotting = TRUE, centrality.type = type, centrality.point.args = list(size = 5, color = "darkred"), centrality.label.args = list(size = 3, nudge_x = 0.4, segment.linetype = 4), centrality.path = TRUE, centrality.path.args = list(linewidth = 1, color = "red", alpha = 0.5), point.args = list(size = 3, alpha = 0.5, na.rm = TRUE), point.path = TRUE, point.path.args = list(alpha = 0.5, linetype = "dashed"), boxplot.args = list(width = 0.2, alpha = 0.5, na.rm = TRUE), violin.args = list(width = 0.5, alpha = 0.2, na.rm = TRUE), ggsignif.args = list(textsize = 3, tip_length = 0.01, na.rm = TRUE), ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
+ggbarstats(data, x, y, counts = NULL, type = "parametric", paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(alpha = 1, fill = "white"), sample.size.label.args = list(size = 4), digits = 2L, proportion.test = results.subtitle, digits.perc = 0L, bf.message = TRUE, ratio = NULL, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, xlab = NULL, ylab = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
+ggbetweenstats(data, x, y, type = "parametric", pairwise.display = "significant", p.adjust.method = "holm", effsize.type = "unbiased", bf.prior = 0.707, bf.message = TRUE, results.subtitle = TRUE, xlab = NULL, ylab = NULL, caption = NULL, title = NULL, subtitle = NULL, digits = 2L, var.equal = FALSE, conf.level = 0.95, nboot = 100L, tr = 0.2, centrality.plotting = TRUE, centrality.type = type, centrality.point.args = list(size = 5, color = "darkred"), centrality.label.args = list(size = 3, nudge_x = 0.4, segment.linetype = 4, min.segment.length = 0), point.args = list(position = ggplot2::position_jitterdodge(dodge.width = 0.6), alpha = 0.4, size = 3, stroke = 0, na.rm = TRUE), boxplot.args = list(width = 0.3, alpha = 0.2, na.rm = TRUE), violin.args = list(width = 0.5, alpha = 0.2, na.rm = TRUE), ggsignif.args = list(textsize = 3, tip_length = 0.01, na.rm = TRUE), ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
+ggcoefstats(x, statistic = NULL, conf.int = TRUE, conf.level = 0.95, digits = 2L, exclude.intercept = FALSE, effectsize.type = "eta", meta.analytic.effect = FALSE, meta.type = "parametric", bf.message = TRUE, sort = "none", xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, only.significant = FALSE, point.args = list(size = 3, color = "blue", na.rm = TRUE), errorbar.args = list(height = 0, na.rm = TRUE), vline = TRUE, vline.args = list(linewidth = 1, linetype = "dashed"), stats.labels = TRUE, stats.label.color = NULL, stats.label.args = list(size = 3, direction = "y", min.segment.length = 0, na.rm = TRUE), package = "RColorBrewer", palette = "Dark2", ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
+ggcorrmat(data, cor.vars = NULL, cor.vars.names = NULL, matrix.type = "upper", type = "parametric", tr = 0.2, partial = FALSE, digits = 2L, sig.level = 0.05, conf.level = 0.95, bf.prior = 0.707, p.adjust.method = "holm", pch = "cross", ggcorrplot.args = list(method = "square", outline.color = "black", pch.cex = 14), package = "RColorBrewer", palette = "Dark2", colors = c("#E69F00", "white", "#009E73"), ggtheme = ggstatsplot::theme_ggstatsplot(), ggplot.component = NULL, title = NULL, subtitle = NULL, caption = NULL, ...)
+ggdotplotstats(data, x, y, xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, digits = 2L, results.subtitle = TRUE, point.args = list(color = "black", size = 3, shape = 16), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), ggplot.component = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), ...)
+gghistostats(data, x, binwidth = NULL, xlab = NULL, title = NULL, subtitle = NULL, caption = NULL, type = "parametric", test.value = 0, bf.prior = 0.707, bf.message = TRUE, effsize.type = "g", conf.level = 0.95, tr = 0.2, digits = 2L, ggtheme = ggstatsplot::theme_ggstatsplot(), results.subtitle = TRUE, bin.args = list(color = "black", fill = "grey50", alpha = 0.7), centrality.plotting = TRUE, centrality.type = type, centrality.line.args = list(color = "blue", linewidth = 1, linetype = "dashed"), normal.curve = FALSE, normal.curve.args = list(linewidth = 2), ggplot.component = NULL, ...)
+ggpiestats(data, x, y = NULL, counts = NULL, type = "parametric", paired = FALSE, results.subtitle = TRUE, label = "percentage", label.args = list(direction = "both"), label.repel = FALSE, digits = 2L, proportion.test = results.subtitle, digits.perc = 0L, bf.message = TRUE, ratio = NULL, conf.level = 0.95, sampling.plan = "indepMulti", fixed.margin = "rows", prior.concentration = 1, title = NULL, subtitle = NULL, caption = NULL, legend.title = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
+ggscatterstats(data, x, y, type = "parametric", conf.level = 0.95, bf.prior = 0.707, bf.message = TRUE, tr = 0.2, digits = 2L, results.subtitle = TRUE, label.var = NULL, label.expression = NULL, marginal = TRUE, point.args = list(size = 3, alpha = 0.4, stroke = 0), point.width.jitter = 0, point.height.jitter = 0, point.label.args = list(size = 3, max.overlaps = 1e+06), smooth.line.args = list(linewidth = 1.5, color = "blue", method = "lm", formula = y ~ x), xsidehistogram.args = list(fill = "#009E73", color = "black", na.rm = TRUE), ysidehistogram.args = list(fill = "#D55E00", color = "black", na.rm = TRUE), xlab = NULL, ylab = NULL, title = NULL, subtitle = NULL, caption = NULL, ggtheme = ggstatsplot::theme_ggstatsplot(), ggplot.component = NULL, ...)
+ggwithinstats(data, x, y, type = "parametric", pairwise.display = "significant", p.adjust.method = "holm", effsize.type = "unbiased", bf.prior = 0.707, bf.message = TRUE, results.subtitle = TRUE, xlab = NULL, ylab = NULL, caption = NULL, title = NULL, subtitle = NULL, digits = 2L, conf.level = 0.95, nboot = 100L, tr = 0.2, centrality.plotting = TRUE, centrality.type = type, centrality.point.args = list(size = 5, color = "darkred"), centrality.label.args = list(size = 3, nudge_x = 0.4, segment.linetype = 4), centrality.path = TRUE, centrality.path.args = list(linewidth = 1, color = "red", alpha = 0.5), point.args = list(size = 3, alpha = 0.5, na.rm = TRUE), point.path = TRUE, point.path.args = list(alpha = 0.5, linetype = "dashed"), boxplot.args = list(width = 0.2, alpha = 0.5, na.rm = TRUE), violin.args = list(width = 0.5, alpha = 0.2, na.rm = TRUE), ggsignif.args = list(textsize = 3, tip_length = 0.01, na.rm = TRUE), ggtheme = ggstatsplot::theme_ggstatsplot(), package = "RColorBrewer", palette = "Dark2", ggplot.component = NULL, ...)
 grouped_ggbarstats(data, ..., grouping.var, plotgrid.args = list(), annotation.args = list())
 grouped_ggbetweenstats(data, ..., grouping.var, plotgrid.args = list(), annotation.args = list())
 grouped_ggcorrmat(data, ..., grouping.var, plotgrid.args = list(), annotation.args = list())

CITATION.cff

@@ -1,5 +1,5 @@
 # -----------------------------------------------------------
-# CITATION file created with {cffr} R package, v0.5.0
+# CITATION file created with {cffr} R package, v1.0.0
 # See also: https://docs.ropensci.org/cffr/
 # -----------------------------------------------------------
 
@@ -17,7 +17,7 @@ abstract: 'Extension of ''ggplot2'', ''ggstatsplot'' creates graphics with detai
   (pie and bar charts) data. Currently, it supports the most common types of statistical
   approaches and tests: parametric, nonparametric, robust, and Bayesian versions of
   t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and
-  regression analyses. References: Patil (2021) <doi:10.21105/joss.03236>.'
+  regression analyses. References: Patil (2021) <https://doi.org/10.21105/joss.03236>.'
 authors:
 - family-names: Patil
   given-names: Indrajeet
@@ -66,11 +66,10 @@ references:
   url: https://www.R-project.org/
   authors:
   - name: R Core Team
-  location:
-    name: Vienna, Austria
-  year: '2024'
   institution:
     name: R Foundation for Statistical Computing
+    address: Vienna, Austria
+  year: '2024'
   version: '>= 4.1.0'
 - type: software
   title: correlation
@@ -209,8 +208,9 @@ references:
   - family-names: Dunnington
     given-names: Dewey
     orcid: https://orcid.org/0000-0002-9415-4582
-  - family-names: van den Brand
+  - family-names: Brand
     given-names: Teun
+    name-particle: van den
     orcid: https://orcid.org/0000-0002-9335-7468
   year: '2024'
   version: '>= 3.5.0'
@@ -277,7 +277,7 @@ references:
   abstract: 'insight: Easy Access to Model Information for Various Model Objects'
   notes: Imports
   url: https://easystats.github.io/insight/
-  repository: https://easystats.r-universe.dev
+  repository: https://CRAN.R-project.org/package=insight
   authors:
   - family-names: Lüdecke
     given-names: Daniel
@@ -442,11 +442,10 @@ references:
   notes: Imports
   authors:
   - name: R Core Team
-  location:
-    name: Vienna, Austria
-  year: '2024'
   institution:
     name: R Foundation for Statistical Computing
+    address: Vienna, Austria
+  year: '2024'
 - type: software
   title: statsExpressions
   abstract: 'statsExpressions: Tidy Dataframes and Expressions with Statistical Details'
@@ -458,7 +457,7 @@ references:
     given-names: Indrajeet
     email: patilindrajeet.science@gmail.com
     orcid: https://orcid.org/0000-0003-1995-6531
-  version: '>= 1.5.3'
+  version: '>= 1.5.3.9000'
   year: '2024'
 - type: software
   title: tidyr
@@ -483,11 +482,10 @@ references:
   notes: Imports
   authors:
   - name: R Core Team
-  location:
-    name: Vienna, Austria
-  year: '2024'
   institution:
     name: R Foundation for Statistical Computing
+    address: Vienna, Austria
+  year: '2024'
 - type: software
   title: afex
   abstract: 'afex: Analysis of Factorial Experiments'
@@ -523,7 +521,7 @@ references:
     given-names: Jeffrey N.
     email: jrouder@uci.edu
   year: '2024'
-  version: '>= 0.9.12-4.5'
+  version: '>= 0.9.12-4.7'
 - type: software
   title: gapminder
   abstract: 'gapminder: Data from Gapminder'
@@ -619,19 +617,6 @@ references:
     email: bolker@mcmaster.ca
   - name: R Development Core Team
   year: '2024'
-- type: software
-  title: PMCMRplus
-  abstract: 'PMCMRplus: Calculate Pairwise Multiple Comparisons of Mean Rank Sums
-    Extended'
-  notes: Suggests
-  repository: https://CRAN.R-project.org/package=PMCMRplus
-  authors:
-  - family-names: Pohlert
-    given-names: Thorsten
-    email: thorsten.pohlert@gmx.de
-    orcid: https://orcid.org/0000-0003-3855-3025
-  year: '2024'
-  version: '>= 1.9.10'
 - type: software
   title: psych
   abstract: 'psych: Procedures for Psychological, Psychometric, and Personality Research'

DESCRIPTION

@@ -48,20 +48,19 @@ Imports:
     purrr (>= 1.0.2),
     rlang,
     stats,
-    statsExpressions (>= 1.5.3),
+    statsExpressions (>= 1.5.3.9000),
     tidyr (>= 1.3.0),
     utils
 Suggests:
     afex,
-    BayesFactor (>= 0.9.12-4.5),
+    BayesFactor (>= 0.9.12-4.7),
     gapminder,
     knitr,
     lme4 (>= 1.1-35.1),
     MASS,
     metaBMA,
     metafor,
     metaplus,
-    PMCMRplus (>= 1.9.10),
     psych,
     rmarkdown,
     rstantools,
@@ -72,6 +71,7 @@ Suggests:
     withr,
     WRS2
 Remotes:
+    IndrajeetPatil/statsExpressions,
     tidyverse/ggplot2
 VignetteBuilder: 
     knitr

NEWS.md

@@ -5,6 +5,14 @@ N.B. All statistical analysis in `{ggstatsplot}` is carried out in
 read the `NEWS` for that package:
 <https://indrajeetpatil.github.io/statsExpressions/news/index.html>
 
+## MAJOR CHANGES
+
+- The cryptic but very useful parameter `k` has been renamed to `digits` to
+  improve its discoverability.
+
+- To be consistent with other functions, `ggpiestats()` and `ggbarstats()` now
+  default to two-sided alternative hypothesis.
+
 # ggstatsplot 0.12.2
 
 - No user-visible changes. Maintenance-only release.
@@ -1386,7 +1394,7 @@ This uncoupling is designed to achieve two things:
     omega-squared effect sizes for anovas, in addition to the prior partial
     variants of these effect sizes.
 
-  - `ggpiestats` gains `perc.k` argument to show desired number of decimal
+  - `ggpiestats` gains `digits.perc` argument to show desired number of decimal
     places in percentage labels.
 
 ## BUG FIXES

R/extract-stats.R

@@ -25,7 +25,7 @@
 #'
 #' @autoglobal
 #'
-#' @examplesIf identical(Sys.getenv("NOT_CRAN"), "true") && requireNamespace("PMCMRplus", quietly = TRUE)
+#' @examplesIf identical(Sys.getenv("NOT_CRAN"), "true")
 #' set.seed(123)
 #'
 #' # non-grouped plot

R/ggbarstats.R

@@ -49,9 +49,9 @@ ggbarstats <- function(
     label = "percentage",
     label.args = list(alpha = 1.0, fill = "white"),
     sample.size.label.args = list(size = 4.0),
-    k = 2L,
+    digits = 2L,
     proportion.test = results.subtitle,
-    perc.k = 0L,
+    digits.perc = 0L,
     bf.message = TRUE,
     ratio = NULL,
     conf.level = 0.95,
@@ -94,15 +94,15 @@ ggbarstats <- function(
 
   if (results.subtitle) {
     .f.args <- list(
-      data                = data,
-      x                   = {{ x }},
-      y                   = {{ y }},
-      conf.level          = conf.level,
-      k                   = k,
-      paired              = paired,
-      ratio               = ratio,
-      sampling.plan       = sampling.plan,
-      fixed.margin        = fixed.margin,
+      data = data,
+      x = {{ x }},
+      y = {{ y }},
+      conf.level = conf.level,
+      digits = digits,
+      paired = paired,
+      ratio = ratio,
+      sampling.plan = sampling.plan,
+      fixed.margin = fixed.margin,
       prior.concentration = prior.concentration
     )
 
@@ -119,10 +119,10 @@ ggbarstats <- function(
   # plot ------------------------------------------
 
   # data frame with summary labels
-  descriptive_df <- descriptive_data(data, {{ x }}, {{ y }}, label, perc.k)
+  descriptive_df <- descriptive_data(data, {{ x }}, {{ y }}, label, digits.perc)
 
   # data frame containing all details needed for prop test
-  onesample_df <- onesample_data(data, {{ x }}, {{ y }}, k)
+  onesample_df <- onesample_data(data, {{ x }}, {{ y }}, digits)
 
   # if no. of factor levels is greater than the default palette color count
   .is_palette_sufficient(package, palette, nlevels(pull(data, {{ x }})))