Package 'ggstatsplot'

A list containing ggplot objects.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

A list of additional arguments passed to patchwork::plot_annotation().

A string specifying how guides should be treated in the layout. 'collect' will collect guides below to the given nesting level, removing duplicates. 'keep' will stop collection at this level and let guides be placed alongside their plot. auto will allow guides to be collected if a upper level tries, but place them alongside the plot if not. If you modify default guide "position" with theme(legend.position=...) while also collecting guides you must apply that change to the overall patchwork (see example).

Currently ignored.

A plot from {ggstatsplot}.

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

The variable to use as the rows in the contingency table. Note that empty factor levels are not dropped: they are shown in the legend and counted (with zero observations) in the statistical test. Use droplevels() beforehand if this is not intended.

The variable to use as the columns in the contingency table. If NULL (default), a one-sample proportion test (a goodness of fit test) is run for the x variable. Otherwise, an appropriate association test is run.

The variable in data containing counts, or NULL if each row represents a single observation.

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE). Only relevant for two-way tables (i.e., when y is supplied), and paired designs are only supported for frequentist tests (McNemar's test). For a two-way table with type = "bayes", paired is ignored and the Bayesian test of independence for unpaired data is run instead. For one-way tables (y = NULL), paired has no effect.

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

Character that decides what each label displays: "percentage" (default), "counts", or "both".

A list of additional aesthetic arguments passed to ggplot2::geom_label().

A list of additional aesthetic arguments passed to ggplot2::geom_text().

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Logical that decides whether a proportion test for x is carried out for each level of y. Defaults to results.subtitle. ggbarstats() displays only the p-values from this test. Always FALSE when type = "bayes", when y is NULL, or when x has only one level.

Number of decimal places for percentage labels (Default: 0L).

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for non-Bayesian types and unpaired designs (paired = FALSE) (Default: TRUE).

A vector of proportions: the expected proportions for the proportion test (should sum to 1). Default is NULL, which means the null is equal theoretical proportions across the levels of the nominal variable. E.g., ratio = c(0.5, 0.5) for two levels, ratio = c(0.25, 0.25, 0.25, 0.25) for four levels, etc.

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

Title text for the legend. If NULL (default), the name of the x variable is used.

Label for x axis. If NULL (default), the name of the y variable is used (no label if y is NULL), since bars are drawn for each level of y.

Label for y axis. If NULL (default), no label is shown.

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

Currently ignored.

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

The grouping (or independent) variable from data.

The response (or outcome or dependent) variable from data.

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

Decides which pairwise comparisons to display. Available options are:

• "significant" (abbreviation accepted: "s")

• "non-significant" (abbreviation accepted: "ns")

• "all"

• "none"

Use this to keep the plot uncluttered when many groups are compared. Pairwise comparisons are carried out (and displayed) only when x has three or more levels. For type = "bayes", there are no p-values, so all comparisons are displayed unless this is "none".

Numeric alpha threshold used to decide which pairwise comparisons are displayed when pairwise.display = "significant" or pairwise.display = "non-significant" (Default: 0.05). It is compared against p-values adjusted using p.adjust.method.

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

Label for x axis variable. If NULL (default), variable name for x will be used.

Label for y axis variable. If NULL (default), variable name for y will be used.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

A list of additional aesthetic arguments passed to ggplot2::geom_point() and ggrepel::geom_label_repel(), respectively, which display the centrality measure.

A list of additional aesthetic arguments passed to ggplot2::geom_point().

A list of additional aesthetic arguments passed to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). Use coef to change this, e.g., boxplot.args = list(coef = 3) extends the whiskers to the most extreme observations within 3 * IQR of the hinges.

A list of additional aesthetic arguments passed to ggplot2::geom_violin().

A list of additional aesthetic arguments passed to ggsignif::geom_signif().

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

Currently ignored.

A model object to be tidied, or a tidy data frame from a regression model. Function internally uses parameters::model_parameters() to get a tidy data frame. If a data frame, it must contain a column named estimate (estimates of coefficients or other quantities of interest). A term column (names of predictors) is recommended; if absent, terms are named term_1, term_2, etc. Columns conf.low and conf.high are needed for error bars, statistic and p.value for labels, and std.error for meta-analysis.

Relevant statistic for the model ("t", "f", "z", or "chi") in the label. Relevant only if x is a data frame; if it is NULL (default), no labels are shown for data frames.

Logical that decides whether to display confidence intervals as error bars (Default: TRUE).

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Logical that decides whether the intercept should be excluded from the plot (Default: FALSE).

Effect size for ANOVA-like objects, passed as the es_type argument of parameters::model_parameters() (Default: "omega", the unbiased estimator).

Logical that decides whether to display a subtitle with results from a meta-analysis via linear (mixed-effects) models (Default: FALSE). If TRUE, subtitle is ignored. This is mostly relevant if a data frame with estimates and their standard errors is entered.

Type of statistics used to carry out random-effects meta-analysis. If "parametric" (default), metafor::rma() will be used. If "robust", metaplus::metaplus() will be used. If "bayes", metaBMA::meta_random() will be used.

Logical that decides whether results from running a Bayesian meta-analysis assuming that the effect size d varies across studies with standard deviation t (i.e., a random-effects analysis) are displayed in the caption. Relevant only if meta.analytic.effect = TRUE and meta.type = "parametric" (Default: TRUE).

If "none" (default), do not sort; if "ascending" or "descending", sort by increasing or decreasing coefficient value, respectively.

Label for x axis. If NULL (default), "estimate" is used.

Label for y axis. If NULL (default), "term" is used.

The text for the plot title.

The text for the plot subtitle. Ignored if meta.analytic.effect = TRUE.

The text for the plot caption. It will be replaced by model fit indices (AIC and BIC), if available, or by the Bayesian meta-analysis results (see bf.message).

If TRUE, only stats labels for significant effects (p < 0.05) are shown (Default: FALSE). This can be helpful when a large number of regression coefficients are to be displayed in a single plot.

A list of additional aesthetic arguments passed to ggplot2::geom_point().

A list of additional arguments passed to ggplot2::geom_errorbar().

Logical that decides whether to display a vertical line at 0 (Default: TRUE).

A list of additional arguments passed to ggplot2::geom_vline().

Logical that decides whether the statistic and p-value for each coefficient are attached to its dot as a label using {ggrepel} (Default: TRUE).

Color for the labels: either a single color or a vector with one color per term. If set to NULL (default), colors will be chosen from the specified palette.

A list of additional arguments passed to ggrepel::geom_label_repel().

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Additional arguments passed to parameters::model_parameters().

A data frame from which variables specified are to be taken.

Variables for which the correlation matrix is to be computed and visualized, specified using {tidyselect} syntax (e.g., c(var1, var2) or starts_with("Sepal")). If NULL (default), all numeric variables from data will be used.

Optional list of names to be used for cor.vars. The names should be entered in the same order.

Character, "upper" (default), "lower", or "full", to display the upper triangular, lower triangular, or full matrix, respectively.

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

Can be TRUE for partial correlations. For Bayesian partial correlations, "full" instead of pseudo-Bayesian partial correlations (i.e., Bayesian correlation based on frequentist partialization) are returned.

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Significance level (Default: 0.05). If the (adjusted; see p.adjust.method) p-value is bigger than sig.level, then the corresponding correlation coefficient is regarded as insignificant and flagged as such in the plot. Ignored for type = "bayes".

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

A character vector of exactly three colors for the gradient: low (negative correlations), mid (zero), and high (positive correlations). Must be a diverging palette so that the sign of the correlation is visually obvious. Default: c("#EA4335", "white", "#4285F4") (red-white-blue).

Decides the point shape to be used for insignificant correlation coefficients. Default: pch = "cross". The caption explaining the insignificance marker is added only for pch = "cross" (or 4).

A list of additional (mostly aesthetic) arguments passed to ggcorrplot::ggcorrplot(). Do not include the following arguments, which are set internally: corr, p.mat, sig.level, ggtheme, colors, type, lab, pch, legend.title, digits.

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

The text for the plot title.

The text for the plot subtitle.

The text for the plot caption. If the insignificance marker caption is shown (see pch), this text is displayed above it.

Additional arguments (currently ignored).

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

A numeric variable from the data frame data.

Label or grouping variable. Each level of y is shown as a single dot: if a level has several rows, x is summarized using the centrality measure for the chosen type (see above), and the one-sample test is then carried out on these per-level summaries (i.e., the sample size is the number of levels of y).

Label for x axis variable. If NULL (default), variable name for x will be used.

Label for y axis variable. If NULL (default), variable name for y will be used.

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

A number indicating the true value of the mean (Default: 0).

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

Logical that decides whether to display confidence intervals as error bars (Default: TRUE).

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

A list of additional aesthetic arguments passed to ggplot2::geom_point().

A list of additional arguments passed to ggplot2::geom_errorbar().

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

A list of additional aesthetic arguments passed to ggplot2::geom_vline(), which displays the line for the centrality measure.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Currently ignored.

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

A numeric variable from the data frame data.

The width of the histogram bins. Can be specified as a numeric value, or a function that calculates width from x. The default is to use (max(x) - min(x)) / sqrt(N). If all values of x are identical, 0.1 (or abs(x) / 1000, if larger) is used instead. You should always check this value and explore multiple widths to find the one that best illustrates the stories in your data.

Label for x axis variable. If NULL (default), variable name for x will be used.

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

A number indicating the true value of the mean (Default: 0).

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

A list of additional aesthetic arguments passed to ggplot2::stat_bin(), which displays the bins. Use the dedicated binwidth argument (not this list) to set the bin width.

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

A list of additional aesthetic arguments passed to ggplot2::geom_vline(), which displays the line for the centrality measure.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

Currently ignored.

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

The variable to use as the rows in the contingency table. Note that empty factor levels are not dropped: they are shown in the legend and counted (with zero observations) in the statistical test. Use droplevels() beforehand if this is not intended.

The variable to use as the columns in the contingency table. If NULL (default), a one-sample proportion test (a goodness of fit test) is run for the x variable. Otherwise, an appropriate association test is run.

The variable in data containing counts, or NULL if each row represents a single observation.

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE). Only relevant for two-way tables (i.e., when y is supplied), and paired designs are only supported for frequentist tests (McNemar's test). For a two-way table with type = "bayes", paired is ignored and the Bayesian test of independence for unpaired data is run instead. For one-way tables (y = NULL), paired has no effect.

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

Character that decides what each label displays: "percentage" (default), "counts", or "both".

A list of additional aesthetic arguments passed to ggplot2::geom_label() (or ggrepel::geom_label_repel() if label.repel = TRUE).

Logical that decides whether labels are repelled using {ggrepel} to avoid overlaps (Default: FALSE).

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Logical that decides whether a proportion test for x is carried out for each level of y. Defaults to results.subtitle. ggbarstats() displays only the p-values from this test. Always FALSE when type = "bayes", when y is NULL, or when x has only one level.

Number of decimal places for percentage labels (Default: 0L).

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for non-Bayesian types and unpaired designs (paired = FALSE) (Default: TRUE).

A vector of proportions: the expected proportions for the proportion test (should sum to 1). Default is NULL, which means the null is equal theoretical proportions across the levels of the nominal variable. E.g., ratio = c(0.5, 0.5) for two levels, ratio = c(0.25, 0.25, 0.25, 0.25) for four levels, etc.

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

Title text for the legend. If NULL (default), the name of the x variable is used.

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

Currently ignored.

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

The column in data containing the explanatory variable to be plotted on the x-axis.

The column in data containing the response (outcome) variable to be plotted on the y-axis.

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

Variable to use for point labels entered as a symbol (e.g. var1).

An expression evaluating to a logical vector that determines the subset of data points to label (e.g. y < 4 & z < 20). While using this argument with purrr::pmap(), you will have to provide a quoted expression (e.g. quote(y < 4 & z < 20)).

Logical that decides whether marginal distributions are plotted on the axes using {ggside} (Default: TRUE).

A list of additional aesthetic arguments passed to ggplot2::geom_point().

Amount of jitter (in data units) in x and y direction, respectively, passed to ggplot2::position_jitter() (Default: 0, i.e., no jitter). Do not specify the jitter in point.args, because it is shared by the points and their labels.

A list of additional aesthetic arguments passed to ggrepel::geom_label_repel(), which displays the point labels.

A list of additional aesthetic arguments passed to ggplot2::geom_smooth(), which displays the regression line. Its confidence band uses conf.level.

A list of arguments passed to ggside::geom_xsidehistogram() and ggside::geom_ysidehistogram(), respectively, to change the marginal histograms.

A list of arguments passed to ggside::scale_xsidey_continuous() and ggside::scale_ysidex_continuous(), respectively, to control the scale of marginal histograms (e.g., breaks, limits, transform). Default is list() (no modifications).

Label for x axis variable. If NULL (default), variable name for x will be used.

Label for y axis variable. If NULL (default), variable name for y will be used.

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

Additional arguments (currently ignored).

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

The condition (or repeated-measures) variable from data.

The response (or outcome or dependent) variable from data.

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

The subject (or repeated measures) identifier from data. Each subject must appear at most once per level of x. If NULL (default), observations are paired by their row order within each level of x. If you are not sure the data are sorted this way, specify this argument. Rows with a missing x or subject.id are ignored, and subjects with a missing (NA) dependent variable in any condition are dropped list-wise (see statsExpressions::complete_subjects()), so the plot, its labels, and the statistical results are all based on the same complete subjects.

Decides which pairwise comparisons to display. Available options are:

• "significant" (abbreviation accepted: "s")

• "non-significant" (abbreviation accepted: "ns")

• "all"

• "none"

Use this to keep the plot uncluttered when many groups are compared. Pairwise comparisons are carried out (and displayed) only when x has three or more levels. For type = "bayes", there are no p-values, so all comparisons are displayed unless this is "none".

Numeric alpha threshold used to decide which pairwise comparisons are displayed when pairwise.display = "significant" or pairwise.display = "non-significant" (Default: 0.05). It is compared against p-values adjusted using p.adjust.method.

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

Label for x axis variable. If NULL (default), variable name for x will be used.

Label for y axis variable. If NULL (default), variable name for y will be used.

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

The text for the plot title.

The text for the plot subtitle. Used only if results.subtitle = FALSE.

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

A list of additional aesthetic arguments passed to ggplot2::geom_point() and ggrepel::geom_label_repel(), respectively, which display the centrality measure.

A list of additional aesthetic arguments passed to ggplot2::geom_path() connecting centrality measures and raw data points, respectively.

A list of additional aesthetic arguments passed to ggplot2::geom_point().

Logical that decides whether individual data points and centrality measures, respectively, are connected using ggplot2::geom_path() (Default: TRUE). point.path is relevant only when there are two groups (i.e., for a t-test). With many data points, consider point.path = FALSE, as these lines can overwhelm the plot.

A list of additional aesthetic arguments passed to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). Use coef to change this, e.g., boxplot.args = list(coef = 3) extends the whiskers to the most extreme observations within 3 * IQR of the hinges.

A list of additional aesthetic arguments passed to ggplot2::geom_violin().

A list of additional aesthetic arguments passed to ggsignif::geom_signif().

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

Currently ignored.

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

Arguments passed on to ggbarstats

label.args

A list of additional aesthetic arguments passed to ggplot2::geom_label().

sample.size.label.args

A list of additional aesthetic arguments passed to ggplot2::geom_text().

xlab

Label for x axis. If NULL (default), the name of the y variable is used (no label if y is NULL), since bars are drawn for each level of y.

ylab

Label for y axis. If NULL (default), no label is shown.

x

The variable to use as the rows in the contingency table. Note that empty factor levels are not dropped: they are shown in the legend and counted (with zero observations) in the statistical test. Use droplevels() beforehand if this is not intended.

y

The variable to use as the columns in the contingency table. If NULL (default), a one-sample proportion test (a goodness of fit test) is run for the x variable. Otherwise, an appropriate association test is run.

proportion.test

Logical that decides whether a proportion test for x is carried out for each level of y. Defaults to results.subtitle. ggbarstats() displays only the p-values from this test. Always FALSE when type = "bayes", when y is NULL, or when x has only one level.

bf.message

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for non-Bayesian types and unpaired designs (paired = FALSE) (Default: TRUE).

digits.perc

Number of decimal places for percentage labels (Default: 0L).

label

Character that decides what each label displays: "percentage" (default), "counts", or "both".

legend.title

Title text for the legend. If NULL (default), the name of the x variable is used.

p.adjust.method

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

results.subtitle

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

subtitle

The text for the plot subtitle. Used only if results.subtitle = FALSE.

caption

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

ggplot.component

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

palette

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

ggtheme

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

digits

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

conf.level

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

paired

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE). Only relevant for two-way tables (i.e., when y is supplied), and paired designs are only supported for frequentist tests (McNemar's test). For a two-way table with type = "bayes", paired is ignored and the Bayesian test of independence for unpaired data is run instead. For one-way tables (y = NULL), paired has no effect.

counts

The variable in data containing counts, or NULL if each row represents a single observation.

ratio

A vector of proportions: the expected proportions for the proportion test (should sum to 1). Default is NULL, which means the null is equal theoretical proportions across the levels of the nominal variable. E.g., ratio = c(0.5, 0.5) for two levels, ratio = c(0.25, 0.25, 0.25, 0.25) for four levels, etc.

A single grouping variable. A separate plot is created for each of its levels (in factor level order, or in order of appearance for character variables). Rows with a missing value in this variable are removed.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

A list of additional arguments passed to patchwork::plot_annotation().

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

Arguments passed on to ggbetweenstats

xlab

Label for x axis variable. If NULL (default), variable name for x will be used.

ylab

Label for y axis variable. If NULL (default), variable name for y will be used.

p.adjust.method

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

pairwise.display

Decides which pairwise comparisons to display. Available options are:

• "significant" (abbreviation accepted: "s")

• "non-significant" (abbreviation accepted: "ns")

• "all"

• "none"

Use this to keep the plot uncluttered when many groups are compared. Pairwise comparisons are carried out (and displayed) only when x has three or more levels. For type = "bayes", there are no p-values, so all comparisons are displayed unless this is "none".

pairwise.alpha

Numeric alpha threshold used to decide which pairwise comparisons are displayed when pairwise.display = "significant" or pairwise.display = "non-significant" (Default: 0.05). It is compared against p-values adjusted using p.adjust.method.

bf.message

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

results.subtitle

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

subtitle

The text for the plot subtitle. Used only if results.subtitle = FALSE.

caption

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

centrality.plotting

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

centrality.type

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

point.args

A list of additional aesthetic arguments passed to ggplot2::geom_point().

boxplot.args

A list of additional aesthetic arguments passed to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). Use coef to change this, e.g., boxplot.args = list(coef = 3) extends the whiskers to the most extreme observations within 3 * IQR of the hinges.

violin.args

A list of additional aesthetic arguments passed to ggplot2::geom_violin().

ggplot.component

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

palette

Name of the discrete palette in "package::palette" format to be used for coloring (via {paletteer}). Run View(paletteer::palettes_d_names) to see all available options.

centrality.point.args,centrality.label.args

A list of additional aesthetic arguments passed to ggplot2::geom_point() and ggrepel::geom_label_repel(), respectively, which display the centrality measure.

ggsignif.args

A list of additional aesthetic arguments passed to ggsignif::geom_signif().

ggtheme

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

x

The grouping (or independent) variable from data.

y

The response (or outcome or dependent) variable from data.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

digits

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

conf.level

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

tr

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

A single grouping variable. A separate plot is created for each of its levels (in factor level order, or in order of appearance for character variables). Rows with a missing value in this variable are removed.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

A list of additional arguments passed to patchwork::plot_annotation().

A data frame from which variables specified are to be taken.

Arguments passed on to ggcorrmat

cor.vars

Variables for which the correlation matrix is to be computed and visualized, specified using {tidyselect} syntax (e.g., c(var1, var2) or starts_with("Sepal")). If NULL (default), all numeric variables from data will be used.

cor.vars.names

Optional list of names to be used for cor.vars. The names should be entered in the same order.

partial

Can be TRUE for partial correlations. For Bayesian partial correlations, "full" instead of pseudo-Bayesian partial correlations (i.e., Bayesian correlation based on frequentist partialization) are returned.

matrix.type

Character, "upper" (default), "lower", or "full", to display the upper triangular, lower triangular, or full matrix, respectively.

sig.level

Significance level (Default: 0.05). If the (adjusted; see p.adjust.method) p-value is bigger than sig.level, then the corresponding correlation coefficient is regarded as insignificant and flagged as such in the plot. Ignored for type = "bayes".

pch

Decides the point shape to be used for insignificant correlation coefficients. Default: pch = "cross". The caption explaining the insignificance marker is added only for pch = "cross" (or 4).

colors

A character vector of exactly three colors for the gradient: low (negative correlations), mid (zero), and high (positive correlations). Must be a diverging palette so that the sign of the correlation is visually obvious. Default: c("#EA4335", "white", "#4285F4") (red-white-blue).

ggcorrplot.args

A list of additional (mostly aesthetic) arguments passed to ggcorrplot::ggcorrplot(). Do not include the following arguments, which are set internally: corr, p.mat, sig.level, ggtheme, colors, type, lab, pch, legend.title, digits.

subtitle

The text for the plot subtitle.

caption

The text for the plot caption. If the insignificance marker caption is shown (see pch), this text is displayed above it.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

digits

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

conf.level

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

tr

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

p.adjust.method

Adjustment method for p-values for multiple comparisons. Possible methods are: "holm" (default), "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr", "none".

ggplot.component

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

ggtheme

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

A single grouping variable. A separate plot is created for each of its levels (in factor level order, or in order of appearance for character variables). Rows with a missing value in this variable are removed.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

A list of additional arguments passed to patchwork::plot_annotation().

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

Arguments passed on to ggdotplotstats

y

Label or grouping variable. Each level of y is shown as a single dot: if a level has several rows, x is summarized using the centrality measure for the chosen type (see above), and the one-sample test is then carried out on these per-level summaries (i.e., the sample size is the number of levels of y).

centrality.line.args

A list of additional aesthetic arguments passed to ggplot2::geom_vline(), which displays the line for the centrality measure.

x

A numeric variable from the data frame data.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

test.value

A number indicating the true value of the mean (Default: 0).

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

digits

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

conf.level

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

tr

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

xlab

Label for x axis variable. If NULL (default), variable name for x will be used.

bf.message

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

results.subtitle

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

subtitle

The text for the plot subtitle. Used only if results.subtitle = FALSE.

caption

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

centrality.plotting

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

centrality.type

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

ggplot.component

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

ggtheme

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.

ylab

Label for y axis variable. If NULL (default), variable name for y will be used.

point.args

A list of additional aesthetic arguments passed to ggplot2::geom_point().

conf.int

Logical that decides whether to display confidence intervals as error bars (Default: TRUE).

errorbar.args

A list of additional arguments passed to ggplot2::geom_errorbar().

A single grouping variable. A separate plot is created for each of its levels (in factor level order, or in order of appearance for character variables). Rows with a missing value in this variable are removed.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

A list of additional arguments passed to patchwork::plot_annotation().

A data frame (or a tibble) from which variables specified are to be taken. Other data types (e.g., matrix, table, array, etc.) will not be accepted. Additionally, grouped data frames from {dplyr} should be ungrouped before they are entered as data.

A numeric variable from the data frame data.

A single grouping variable. A separate plot is created for each of its levels (in factor level order, or in order of appearance for character variables). Rows with a missing value in this variable are removed.

The width of the histogram bins (see gghistostats()). If NULL (default), it is computed once from the non-missing values of x in the full data (not per group), so that all plots share the same bin width.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides, which has its own argument.

A list of additional arguments passed to patchwork::plot_annotation().

Arguments passed on to gghistostats

bin.args

A list of additional aesthetic arguments passed to ggplot2::stat_bin(), which displays the bins. Use the dedicated binwidth argument (not this list) to set the bin width.

centrality.line.args

A list of additional aesthetic arguments passed to ggplot2::geom_vline(), which displays the line for the centrality measure.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter (e.g. "np" or "bf"). Matching is on the initial lowercase letter only, so any other value (including capitalized values such as "Bayes") falls back to "parametric" without a warning.

test.value

A number indicating the true value of the mean (Default: 0).

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.

digits

Number of digits for rounding or significant figures. May also be "signif" to return significant figures or "scientific" to return scientific notation. Control the number of digits by adding the value as suffix, e.g. digits = "scientific4" to have scientific notation with 4 decimal places, or digits = "signif5" for 5 significant figures (see also signif()).

conf.level

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95).

tr

Trim level for the mean when carrying out robust tests. In case of an error, try reducing the value of tr, which is by default set to 0.2. Lowering the value might help.

bf.prior

A number between 0.5 and 2 (default 0.707), the prior width to use in calculating Bayes factors and posterior estimates. In addition to numeric arguments, several named values are also recognized: "medium", "wide", and "ultrawide", corresponding to r scale values of 1/2, sqrt(2)/2, and 1, respectively. In case of an ANOVA, this value corresponds to scale for fixed effects.

xlab

Label for x axis variable. If NULL (default), variable name for x will be used.

bf.message

Logical that decides whether to display the Bayes Factor in favor of the null hypothesis as a caption. Relevant only for parametric tests (Default: TRUE).

results.subtitle

Logical that decides whether the results of statistical tests are displayed as a subtitle (Default: TRUE). Setting this to FALSE also skips the automatic Bayes Factor caption. Other plot details have their own arguments.

subtitle

The text for the plot subtitle. Used only if results.subtitle = FALSE.

caption

The text for the plot caption. It will be replaced by the Bayes Factor caption whenever that is displayed (see bf.message).

centrality.plotting

Logical that decides whether central tendency measure is to be displayed as a point with a label (Default: TRUE). Function decides which central tendency measure to show depending on the type argument.

• mean for parametric statistics

• median for non-parametric statistics

• trimmed mean for robust statistics

• MAP estimator for Bayesian statistics

Use centrality.type to choose a different centrality measure.

centrality.type

Decides which centrality measure is displayed. Defaults to the same value as type. Can be one of:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

As with type, abbreviations are accepted.

ggplot.component

A {ggplot2} component, or a list of components, to add to the plot (Default: NULL). This is mostly helpful for the grouped_ variants, where it is applied to each individual plot.

ggtheme

A {ggplot2} theme (Default: theme_ggstatsplot()). Any {ggplot2} theme (e.g., ggplot2::theme_bw()) or theme from an extension package (e.g., ggthemes::theme_fivethirtyeight()) can be used. Note that some themes remove plot details. For example, ggthemes::theme_fivethirtyeight() removes the secondary Y-axis, which ggbetweenstats() uses to show details about pairwise comparisons.