Package {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.

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 containing ggplot objects.

A list of additional arguments passed to patchwork::wrap_plots(), except for guides argument which is already separately specified here.

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} package

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. Default is NULL. If NULL, one-sample proportion test (a goodness of fit test) will be run for the x variable. Otherwise an appropriate association test will be 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.

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE).

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

Character decides what information needs to be displayed on the label in each pie slice. Possible options are "percentage" (default), "counts", "both".

Additional aesthetic arguments that will be passed to ggplot2::geom_label().

Additional aesthetic arguments that will be 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()).

Decides whether proportion test for x variable is to be carried out for each level of y. Defaults to results.subtitle. In ggbarstats(), only p-values from this test will be displayed. Always FALSE when type = "bayes" or when y is NULL.

Numeric that decides number of decimal places for percentage labels (Default: 0L).

Logical that decides whether to display Bayes Factor in favor of the null hypothesis as a caption. This argument is 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). If NULL, no confidence intervals will be computed.

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. Will work 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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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. In case of a repeated measures or within-subjects design, if subject.id argument is not available or not explicitly specified, the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted, the results can be inaccurate when there are more than two levels in x and there are NAs present. The data is expected to be sorted by user in subject-1, subject-2, ..., pattern.

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.

Decides which pairwise comparisons to display. Available options are:

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

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

• "all"

• "none"

You can use this argument to make sure that your plot is not uber-cluttered when you have multiple groups being compared and scores of pairwise comparisons being displayed. 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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

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

Labels 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. Will work 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). If NULL, no confidence intervals will be computed.

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 centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

A list of additional aesthetic arguments to be passed to ggplot2::geom_point() and ggrepel::geom_label_repel() geoms, which are involved in centrality plotting.

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

A list of additional aesthetic arguments passed on to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). To customize whisker length, you can use the coef parameter, e.g., boxplot.args = list(coef = 3) for whiskers extending to 3 * IQR, or boxplot.args = list(coef = 0) to show only the range of the data.

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

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

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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. Decides whether to display confidence intervals as error bars (Default: TRUE).

Numeric deciding level of confidence or credible intervals (Default: 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).

This is the same as es_type argument of parameters::model_parameters(). Defaults to "omega" (the unbiased estimator), and relevant for ANOVA-like objects.

Logical that decides whether to display a subtitle with results from a meta-analysis via linear (mixed-effects) models (default: FALSE). If TRUE, input to argument subtitle will be ignored. This will be 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) should be displayed in caption. Relevant only if meta.analytic.effect = TRUE and meta.type = "parametric". Defaults to TRUE.

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

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. The input to this argument will be ignored if meta.analytic.effect is set to 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 to be passed to the ggplot2::geom_point().

Additional arguments that will be passed to ggplot2::geom_errorbar() geom. Please see documentation for that function to know more about these arguments.

Decides whether to display a vertical line at 0 (Default: TRUE).

Additional arguments that will be passed to ggplot2::geom_vline() geom. Please see documentation for that function to know more about these arguments.

Logical. Decides whether the statistic and p-values for each coefficient are to be attached to each dot as a text 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.

Additional arguments that will be 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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

Additional arguments to tidying method. For more, see 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.

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). If NULL, no confidence intervals will be computed.

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 that will be passed to ggcorrplot::ggcorrplot() function. The list should avoid any of the following arguments since they are already internally being used: corr, p.mat, sig.level, ggtheme, colors, type, lab, pch, legend.title, digits.

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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.

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.

Labels 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. Will work 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.

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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

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

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95). If NULL, no confidence intervals will be computed.

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()).

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

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

Additional arguments that will be passed to ggplot2::geom_errorbar() geom. Please see documentation for that function to know more about these arguments.

Logical that decides whether centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

A list of additional aesthetic arguments to be passed to the ggplot2::geom_vline() used to display the lines corresponding to the centrality parameter.

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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). You should always check this value and explore multiple widths to find the best to illustrate 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. Will work 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.

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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95). If NULL, no confidence intervals will be computed.

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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

A list of additional aesthetic arguments to be passed to the ggplot2::stat_bin() used to display the bins. Do not specify binwidth argument in this list since it has already been specified using the dedicated argument.

Logical that decides whether centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

A list of additional aesthetic arguments to be passed to the ggplot2::geom_vline() used to display the lines corresponding to the centrality parameter.

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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. Default is NULL. If NULL, one-sample proportion test (a goodness of fit test) will be run for the x variable. Otherwise an appropriate association test will be 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.

Logical indicating whether data came from a within-subjects or repeated measures design study (Default: FALSE).

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

Character decides what information needs to be displayed on the label in each pie slice. Possible options are "percentage" (default), "counts", "both".

Additional aesthetic arguments that will be passed to ggplot2::geom_label() (or ggrepel::geom_label_repel() if label.repel = TRUE).

Whether labels should be repelled using {ggrepel} package. This can be helpful in case of overlapping labels (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()).

Decides whether proportion test for x variable is to be carried out for each level of y. Defaults to results.subtitle. In ggbarstats(), only p-values from this test will be displayed. Always FALSE when type = "bayes" or when y is NULL.

Numeric that decides number of decimal places for percentage labels (Default: 0L).

Logical that decides whether to display Bayes Factor in favor of the null hypothesis as a caption. This argument is 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). If NULL, no confidence intervals will be computed.

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. Will work 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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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.

Scalar between 0 and 1 (default: ⁠95%⁠ confidence/credible intervals, 0.95). If NULL, no confidence intervals will be computed.

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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (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()).

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

Variable to use for points 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)).

Decides whether marginal distributions will be plotted on axes using {ggside} functions. The default is TRUE.

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

Degree of jitter in x and y direction, respectively. Defaults to 0 (0%) of the resolution of the data. Note that the jitter should not be specified in the point.args because this information will be passed to two different geoms: one displaying the points and the other displaying the labels for these points.

A list of additional aesthetic arguments to be passed to ggrepel::geom_label_repel() geom used to display the labels.

A list of additional aesthetic arguments to be passed to ggplot2::geom_smooth() geom used to display the regression line. Its confidence band uses conf.level.

A list of arguments passed to respective geom_s from the {ggside} package to change the marginal distribution histograms plots.

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.

Labels 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. Will work 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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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. In case of a repeated measures or within-subjects design, if subject.id argument is not available or not explicitly specified, the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted, the results can be inaccurate when there are more than two levels in x and there are NAs present. The data is expected to be sorted by user in subject-1, subject-2, ..., pattern.

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.

Across repeated measures conditions, each row in the dataset must correspond to a unique unit (e.g., subject or participant). If your data frame is already in such a format, you can ignore the subject.id argument (the function will use row number to pair observations). But if you are not sure, it is always better to specify this argument. Note that if there are any missing values (i.e., NA) in the dependent variable and the subject.id is not specified, they will be dropped using a list-wise approach. If you specify subject.id, partially observed subjects will still be shown in the plot, but inferential statistics will be computed using only complete repeated-measures pairs.

Decides which pairwise comparisons to display. Available options are:

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

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

• "all"

• "none"

You can use this argument to make sure that your plot is not uber-cluttered when you have multiple groups being compared and scores of pairwise comparisons being displayed. 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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

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

Labels 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. Will work 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). If NULL, no confidence intervals will be computed.

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 centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

A list of additional aesthetic arguments to be passed to ggplot2::geom_point() and ggrepel::geom_label_repel() geoms, which are involved in centrality plotting.

A list of additional aesthetic arguments passed on to ggplot2::geom_path() connecting raw data points and mean points.

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

Logical that decides whether individual data points and means, respectively, should be connected using ggplot2::geom_path(). Both default to TRUE. Note that point.path argument is relevant only when there are two groups (i.e., in case of a t-test). In case of large number of data points, it is advisable to set point.path = FALSE as these lines can overwhelm the plot.

A list of additional aesthetic arguments passed on to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). To customize whisker length, you can use the coef parameter, e.g., boxplot.args = list(coef = 3) for whiskers extending to 3 * IQR, or boxplot.args = list(coef = 0) to show only the range of the data.

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

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

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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

Additional aesthetic arguments that will be passed to ggplot2::geom_label().

sample.size.label.args

Additional aesthetic arguments that will be 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. Default is NULL. If NULL, one-sample proportion test (a goodness of fit test) will be run for the x variable. Otherwise an appropriate association test will be run.

proportion.test

Decides whether proportion test for x variable is to be carried out for each level of y. Defaults to results.subtitle. In ggbarstats(), only p-values from this test will be displayed. Always FALSE when type = "bayes" or when y is NULL.

bf.message

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

digits.perc

Numeric that decides number of decimal places for percentage labels (Default: 0L).

label

Character decides what information needs to be displayed on the label in each pie slice. Possible options are "percentage" (default), "counts", "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

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

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). If NULL, no confidence intervals will be computed.

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).

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 argument which is already separately specified here.

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

Labels 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"

You can use this argument to make sure that your plot is not uber-cluttered when you have multiple groups being compared and scores of pairwise comparisons being displayed. 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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

results.subtitle

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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 centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

centrality.type

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

point.args

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

boxplot.args

A list of additional aesthetic arguments passed on to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). To customize whisker length, you can use the coef parameter, e.g., boxplot.args = list(coef = 3) for whiskers extending to 3 * IQR, or boxplot.args = list(coef = 0) to show only the range of the data.

violin.args

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

ggplot.component

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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 to be passed to ggplot2::geom_point() and ggrepel::geom_label_repel() geoms, which are involved in centrality plotting.

ggsignif.args

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

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

x

The grouping (or independent) variable from data. In case of a repeated measures or within-subjects design, if subject.id argument is not available or not explicitly specified, the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted, the results can be inaccurate when there are more than two levels in x and there are NAs present. The data is expected to be sorted by user in subject-1, subject-2, ..., pattern.

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.

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). If NULL, no confidence intervals will be computed.

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 argument which is already separately specified here.

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 that will be passed to ggcorrplot::ggcorrplot() function. The list should avoid any of the following arguments since they are already internally being used: 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.

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). If NULL, no confidence intervals will be computed.

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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 argument which is already separately specified here.

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 to be passed to the ggplot2::geom_vline() used to display the lines corresponding to the centrality parameter.

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.

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). If NULL, no confidence intervals will be computed.

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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

results.subtitle

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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 centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

centrality.type

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

ggplot.component

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

ylab

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

point.args

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

conf.int

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

errorbar.args

Additional arguments that will be passed to ggplot2::geom_errorbar() geom. Please see documentation for that function to know more about these arguments.

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 argument which is already separately specified here.

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 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 argument which is already separately specified here.

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

Arguments passed on to gghistostats

bin.args

A list of additional aesthetic arguments to be passed to the ggplot2::stat_bin() used to display the bins. Do not specify binwidth argument in this list since it has already been specified using the dedicated argument.

centrality.line.args

A list of additional aesthetic arguments to be passed to the ggplot2::geom_vline() used to display the lines corresponding to the centrality parameter.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

You can specify just the initial letter.

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). If NULL, no confidence intervals will be computed.

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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

results.subtitle

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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 centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

centrality.type

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

ggplot.component

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 ggpiestats

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. Default is NULL. If NULL, one-sample proportion test (a goodness of fit test) will be run for the x variable. Otherwise an appropriate association test will be run.

proportion.test

Decides whether proportion test for x variable is to be carried out for each level of y. Defaults to results.subtitle. In ggbarstats(), only p-values from this test will be displayed. Always FALSE when type = "bayes" or when y is NULL.

bf.message

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

digits.perc

Numeric that decides number of decimal places for percentage labels (Default: 0L).

label

Character decides what information needs to be displayed on the label in each pie slice. Possible options are "percentage" (default), "counts", "both".

label.args

Additional aesthetic arguments that will be passed to ggplot2::geom_label() (or ggrepel::geom_label_repel() if label.repel = TRUE).

label.repel

Whether labels should be repelled using {ggrepel} package. This can be helpful in case of overlapping labels (Default: FALSE).

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

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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 ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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 value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

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). If NULL, no confidence intervals will be computed.

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).

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 argument which is already separately specified here.

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 ggscatterstats

label.var

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

label.expression

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)).

point.label.args

A list of additional aesthetic arguments to be passed to ggrepel::geom_label_repel() geom used to display the labels.

smooth.line.args

A list of additional aesthetic arguments to be passed to ggplot2::geom_smooth() geom used to display the regression line. Its confidence band uses conf.level.

marginal

Decides whether marginal distributions will be plotted on axes using {ggside} functions. The default is TRUE.

point.width.jitter,point.height.jitter

Degree of jitter in x and y direction, respectively. Defaults to 0 (0%) of the resolution of the data. Note that the jitter should not be specified in the point.args because this information will be passed to two different geoms: one displaying the points and the other displaying the labels for these points.

xsidehistogram.args,ysidehistogram.args

A list of arguments passed to respective geom_s from the {ggside} package to change the marginal distribution histograms plots.

xsidehistogram.scale,ysidehistogram.scale

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).

x

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

y

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

type

A character specifying the type of statistical approach:

• "parametric"

• "nonparametric"

• "robust"

• "bayes"

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). If NULL, no confidence intervals will be computed.

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.

ylab

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

bf.message

Logical that decides whether to display Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

results.subtitle

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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).

point.args

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

ggplot.component

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

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 argument which is already separately specified here.

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 ggwithinstats

point.path,centrality.path

Logical that decides whether individual data points and means, respectively, should be connected using ggplot2::geom_path(). Both default to TRUE. Note that point.path argument is relevant only when there are two groups (i.e., in case of a t-test). In case of large number of data points, it is advisable to set point.path = FALSE as these lines can overwhelm the plot.

centrality.path.args,point.path.args

A list of additional aesthetic arguments passed on to ggplot2::geom_path() connecting raw data points and mean points.

subject.id

Across repeated measures conditions, each row in the dataset must correspond to a unique unit (e.g., subject or participant). If your data frame is already in such a format, you can ignore the subject.id argument (the function will use row number to pair observations). But if you are not sure, it is always better to specify this argument. Note that if there are any missing values (i.e., NA) in the dependent variable and the subject.id is not specified, they will be dropped using a list-wise approach. If you specify subject.id, partially observed subjects will still be shown in the plot, but inferential statistics will be computed using only complete repeated-measures pairs.

xlab

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

ylab

Labels 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"

You can use this argument to make sure that your plot is not uber-cluttered when you have multiple groups being compared and scores of pairwise comparisons being displayed. 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 Bayes Factor in favor of the null hypothesis. This argument is relevant only for parametric test (Default: TRUE).

results.subtitle

Decides whether the results of statistical tests are to be displayed as a subtitle (Default: TRUE). If set to FALSE, only the plot will be returned.

subtitle

The text for the plot subtitle. Will work 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 centrality 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

If you want a different centrality parameter, you can specify this using centrality.type argument.

centrality.type

Decides which centrality parameter is to be displayed. The default is to choose the same as type argument. You can specify this to be:

• "parametric" (for mean)

• "nonparametric" (for median)

• "robust" (for trimmed mean)

• "bayes" (for MAP estimator)

Just as type argument, abbreviations are also accepted.

point.args

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

boxplot.args

A list of additional aesthetic arguments passed on to ggplot2::geom_boxplot(). By default, the whiskers extend to 1.5 times the interquartile range (IQR) from the box (Tukey-style). To customize whisker length, you can use the coef parameter, e.g., boxplot.args = list(coef = 3) for whiskers extending to 3 * IQR, or boxplot.args = list(coef = 0) to show only the range of the data.

violin.args

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

ggplot.component

A ggplot component to be added to the plot prepared by {ggstatsplot}. This argument is primarily helpful for grouped_ variants of all primary functions. Default is NULL. The argument should be entered as a {ggplot2} function or a list of {ggplot2} functions.

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 to be passed to ggplot2::geom_point() and ggrepel::geom_label_repel() geoms, which are involved in centrality plotting.

ggsignif.args

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

ggtheme

A {ggplot2} theme. Default value is theme_ggstatsplot(). Any of the {ggplot2} themes (e.g., ggplot2::theme_bw()), or themes from extension packages are allowed (e.g., ggthemes::theme_fivethirtyeight(), hrbrthemes::theme_ipsum_ps(), etc.). But note that sometimes these themes will remove some of the details that {ggstatsplot} plots typically contains. For example, if relevant, ggbetweenstats() shows details about multiple comparison test as a label on the secondary Y-axis. Some themes (e.g. ggthemes::theme_fivethirtyeight()) will remove the secondary Y-axis and thus the details as well.

x

The grouping (or independent) variable from data. In case of a repeated measures or within-subjects design, if subject.id argument is not available or not explicitly specified, the function assumes that the data has already been sorted by such an id by the user and creates an internal identifier. So if your data is not sorted, the results can be inaccurate when there are more than two levels in x and there are NAs present. The data is expected to be sorted by user in subject-1, subject-2, ..., pattern.

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.

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). If NULL, no confidence intervals will be computed.

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 argument which is already separately specified here.

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