Package index • 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
ks_test(): Two-Sample Kolmogorov-Smirnov 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
conover_test(): Conover's All-Pairs Rank Comparison Test
friedman_conover_test(): Conover's All-Pairs Comparisons Test for Friedman Rank Sums
friedman_nemenyi_test(): Nemenyi Post-Hoc Test for Friedman Rank Sums
dunnett_test(): Dunnett's Many-to-One Comparisons Test
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
fligner_test(): Fligner-Killeen 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
add_cld(): Compact Letter Display of All-Pairwise Comparisons
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

rstatix-programming: Programming with rstatix (tidy evaluation)
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