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

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

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