Function reference • rstatix

Descriptive Statistics
`get_summary_stats()`	Compute Summary Statistics
`freq_table()`	Compute Frequency Table
`get_mode()`	Compute Mode
`identify_outliers()` `is_outlier()` `is_extreme()`	Identify Univariate Outliers Using Boxplot Methods
`mahalanobis_distance()`	Compute Mahalanobis Distance and Flag Multivariate Outliers
`shapiro_test()` `mshapiro_test()`	Shapiro-Wilk Normality Test
Comparing Means
`t_test()` `pairwise_t_test()`	T-test
`wilcox_test()` `pairwise_wilcox_test()`	Wilcoxon Tests
`sign_test()` `pairwise_sign_test()`	Sign Test
`anova_test()` `get_anova_table()` `print(<anova_test>)` `plot(<anova_test>)`	Anova Test
`welch_anova_test()`	Welch One-Way ANOVA Test
`kruskal_test()`	Kruskal-Wallis Test
`friedman_test()`	Friedman Rank Sum Test
`get_comparisons()`	Create a List of Possible Comparisons Between Groups
`get_y_position()` `add_y_position()` `add_x_position()` `add_xy_position()`	Autocompute P-value Positions For Plotting Significance
ANOVA helpers
`factorial_design()`	Build Factorial Designs for ANOVA
`anova_summary()`	Create Nice Summary Tables of ANOVA Results
Post-Hoc Analyses
`tukey_hsd()`	Tukey Honest Significant Differences
`dunn_test()`	Dunn's Test of Multiple Comparisons
`games_howell_test()`	Games Howell Post-hoc Tests
`emmeans_test()` `get_emmeans()`	Pairwise Comparisons of Estimated Marginal Means
Comparing Proportions
`prop_test()` `pairwise_prop_test()` `row_wise_prop_test()`	Proportion Test
`chisq_test()` `pairwise_chisq_gof_test()` `pairwise_chisq_test_against_p()` `chisq_descriptives()` `expected_freq()` `observed_freq()` `pearson_residuals()` `std_residuals()`	Chi-squared Test for Count Data
`fisher_test()` `pairwise_fisher_test()` `row_wise_fisher_test()`	Fisher's Exact Test for Count Data
`binom_test()` `pairwise_binom_test()` `pairwise_binom_test_against_p()`	Exact Binomial Test
`multinom_test()`	Exact Multinomial Test
`mcnemar_test()` `pairwise_mcnemar_test()`	McNemar's Chi-squared Test for Count Data
`cochran_qtest()`	Cochran's Q Test
`prop_trend_test()`	Test for Trend in Proportions
Comparing Variances
`levene_test()`	Levene's Test
`box_m()`	Box's M-test for Homogeneity of Covariance Matrices
Effect Size
`cohens_d()`	Compute Cohen's d Measure of Effect Size
`wilcox_effsize()`	Wilcoxon Effect Size
`eta_squared()` `partial_eta_squared()`	Effect Size for ANOVA
`kruskal_effsize()`	Kruskal-Wallis Effect Size
`friedman_effsize()`	Friedman Test Effect Size (Kendall's W Value)
`cramer_v()`	Compute Cramer's V
Correlation analysis
`cor_test()`	Correlation Test
`cor_mat()` `cor_pmat()` `cor_get_pval()`	Compute Correlation Matrix with P-values
`as_cor_mat()`	Convert a Correlation Test Data Frame into a Correlation Matrix
`cor_select()`	Subset Correlation Matrix
`pull_triangle()` `pull_upper_triangle()` `pull_lower_triangle()`	Pull Lower and Upper Triangular Part of a Matrix
`replace_triangle()` `replace_upper_triangle()` `replace_lower_triangle()`	Replace Lower and Upper Triangular Part of a Matrix
`cor_reorder()`	Reorder Correlation Matrix
`cor_gather()` `cor_spread()`	Reshape Correlation Data
`cor_as_symbols()`	Replace Correlation Coefficients by Symbols
`cor_plot()`	Visualize Correlation Matrix Using Base Plot
`cor_mark_significant()`	Add Significance Levels To a Correlation Matrix
Adjust p-values and add significance symbols
`adjust_pvalue()`	Adjust P-values for Multiple Comparisons
`add_significance()`	Add P-value Significance Symbols
`p_round()` `p_format()` `p_mark_significant()` `p_detect()` `p_names()` `p_adj_names()`	Rounding and Formatting p-values
Extract Information From Statistical Tests
`get_pwc_label()` `get_test_label()` `create_test_label()` `get_n()` `get_description()`	Extract Label Information from Statistical Tests
`remove_ns()`	Remove Non-Significant from Statistical Tests
Data Manipulation Helper Functions These functions are internally used in rstatix and in ggpubr R package to make it easy to program with tidyverse packages using non standard evaluation.
`df_select()`	Select Columns in a Data Frame
`df_arrange()`	Arrange Rows by Column Values
`df_group_by()`	Group a Data Frame by One or more Variables
`df_nest_by()`	Nest a Tibble By Groups
`df_split_by()`	Split a Data Frame into Subset
`df_unite()` `df_unite_factors()`	Unite Multiple Columns into One
`df_label_both()` `df_label_value()`	Functions to Label Data Frames by Grouping Variables
`df_get_var_names()`	Get User Specified Variable Names
Others
`reexports` `tibble` `mutate` `filter` `group_by` `select` `desc` `drop_na` `gather` `spread` `tidy` `augment` `Anova`	Objects exported from other packages
`doo()`	Alternative to dplyr::do for Doing Anything
`sample_n_by()`	Sample n Rows By Group From a Table
`convert_as_factor()` `set_ref_level()` `reorder_levels()`	Factors
`make_clean_names()`	Make Clean Names
`counts_to_cases()`	Convert a Table of Counts into a Data Frame of cases

Reference

Descriptive Statistics

Comparing Means

ANOVA helpers

Post-Hoc Analyses

Comparing Proportions

Comparing Variances

Effect Size

Correlation analysis

Adjust p-values and add significance symbols

Extract Information From Statistical Tests

Data Manipulation Helper Functions

Others