Package: rstatix 0.7.2.999

rstatix: Pipe-Friendly Framework for Basic Statistical Tests

Provides a simple and intuitive pipe-friendly framework, coherent with the 'tidyverse' design philosophy, for performing basic statistical tests, including t-test, Wilcoxon test, ANOVA, Kruskal-Wallis and correlation analyses. The output of each test is automatically transformed into a tidy data frame to facilitate visualization. Additional functions are available for reshaping, reordering, manipulating and visualizing correlation matrix. Functions are also included to facilitate the analysis of factorial experiments, including purely 'within-Ss' designs (repeated measures), purely 'between-Ss' designs, and mixed 'within-and-between-Ss' designs. It's also possible to compute several effect size metrics, including "eta squared" for ANOVA, "Cohen's d" for t-test and 'Cramer V' for the association between categorical variables. The package contains helper functions for identifying univariate and multivariate outliers, assessing normality and homogeneity of variances.

Authors:Alboukadel Kassambara [aut, cre]

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NEWS

# Install 'rstatix' in R:
install.packages('rstatix', repos = c('https://kassambara.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/kassambara/rstatix/issues

On CRAN:

15.18 score 447 stars 401 packages 9.2k scripts 204k downloads 123 mentions 126 exports 61 dependencies

Last updated 2 years agofrom:360cda40bd. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-winNOTENov 22 2024
R-4.5-linuxNOTENov 22 2024
R-4.4-winNOTENov 22 2024
R-4.4-macNOTENov 22 2024
R-4.3-winOKNov 22 2024
R-4.3-macOKNov 22 2024

Exports:%>%add_significanceadd_x_positionadd_xy_positionadd_y_positionadjust_pvalueAnovaanova_summaryanova_testas_cor_mataugmentbinom_testbox_mchisq_descriptiveschisq_testcochran_qtestcohens_dconvert_as_factorcor_as_symbolscor_gathercor_get_pvalcor_mark_significantcor_matcor_plotcor_pmatcor_reordercor_selectcor_spreadcor_testcounts_to_casescramer_vcreate_test_labeldescdf_arrangedf_get_var_namesdf_group_bydf_label_bothdf_label_valuedf_nest_bydf_selectdf_split_bydf_unitedf_unite_factorsdoodrop_nadunn_testemmeans_testeta_squaredexpected_freqfactorial_designfilterfisher_testfreq_tablefriedman_effsizefriedman_testgames_howell_testgatherget_anova_tableget_comparisonsget_descriptionget_emmeansget_modeget_nget_pwc_labelget_summary_statsget_test_labelget_y_positiongroup_byidentify_outliersis_extremeis_outlierkruskal_effsizekruskal_testlevene_testmahalanobis_distancemake_clean_namesManovamcnemar_testmshapiro_testmultinom_testmutateobserved_freqp_adj_namesp_detectp_formatp_mark_significantp_namesp_roundpairwise_binom_testpairwise_binom_test_against_ppairwise_chisq_gof_testpairwise_chisq_test_against_ppairwise_fisher_testpairwise_mcnemar_testpairwise_prop_testpairwise_sign_testpairwise_t_testpairwise_wilcox_testpartial_eta_squaredpearson_residualsprop_testprop_trend_testpull_lower_trianglepull_trianglepull_upper_triangleremove_nsreorder_levelsreplace_lower_trianglereplace_trianglereplace_upper_trianglerow_wise_fisher_testrow_wise_prop_testsample_n_byselectset_ref_levelshapiro_testsign_testspreadstd_residualst_testtibbletidytukey_hsdwelch_anova_testwilcox_effsizewilcox_test

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpurrrquantregR6RColorBrewerRcppRcppEigenrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Add P-value Significance Symbolsadd_significance
Adjust P-values for Multiple Comparisonsadjust_pvalue
Create Nice Summary Tables of ANOVA Resultsanova_summary
Anova Testanova_test get_anova_table plot.anova_test print.anova_test
Convert a Correlation Test Data Frame into a Correlation Matrixas_cor_mat
Exact Binomial Testbinom_test pairwise_binom_test pairwise_binom_test_against_p
Box's M-test for Homogeneity of Covariance Matricesbox_m
Chi-squared Test for Count Datachisq_descriptives chisq_test expected_freq observed_freq pairwise_chisq_gof_test pairwise_chisq_test_against_p pearson_residuals std_residuals
Cochran's Q Testcochran_qtest
Compute Cohen's d Measure of Effect Sizecohens_d
Factorsconvert_as_factor reorder_levels set_ref_level
Replace Correlation Coefficients by Symbolscor_as_symbols
Reshape Correlation Datacor_gather cor_spread
Add Significance Levels To a Correlation Matrixcor_mark_significant
Compute Correlation Matrix with P-valuescor_get_pval cor_mat cor_pmat
Visualize Correlation Matrix Using Base Plotcor_plot
Reorder Correlation Matrixcor_reorder
Subset Correlation Matrixcor_select
Correlation Testcor_test
Convert a Table of Counts into a Data Frame of casescounts_to_cases
Compute Cramer's Vcramer_v
Arrange Rows by Column Valuesdf_arrange
Get User Specified Variable Namesdf_get_var_names
Group a Data Frame by One or more Variablesdf_group_by
Functions to Label Data Frames by Grouping Variablesdf_label_both df_label_value
Nest a Tibble By Groupsdf_nest_by
Select Columns in a Data Framedf_select
Split a Data Frame into Subsetdf_split_by
Unite Multiple Columns into Onedf_unite df_unite_factors
Alternative to dplyr::do for Doing Anythingdoo
Dunn's Test of Multiple Comparisonsdunn_test
Pairwise Comparisons of Estimated Marginal Meansemmeans_test get_emmeans
Effect Size for ANOVAeta_squared partial_eta_squared
Build Factorial Designs for ANOVAfactorial_design
Fisher's Exact Test for Count Datafisher_test pairwise_fisher_test row_wise_fisher_test
Compute Frequency Tablefreq_table
Friedman Test Effect Size (Kendall's W Value)friedman_effsize
Friedman Rank Sum Testfriedman_test
Games Howell Post-hoc Testsgames_howell_test
Create a List of Possible Comparisons Between Groupsget_comparisons
Compute Modeget_mode
Extract Label Information from Statistical Testscreate_test_label get_description get_n get_pwc_label get_test_label
Compute Summary Statisticsget_summary_stats
Autocompute P-value Positions For Plotting Significanceadd_xy_position add_x_position add_y_position get_y_position
Identify Univariate Outliers Using Boxplot Methodsidentify_outliers is_extreme is_outlier
Kruskal-Wallis Effect Sizekruskal_effsize
Kruskal-Wallis Testkruskal_test
Levene's Testlevene_test
Compute Mahalanobis Distance and Flag Multivariate Outliersmahalanobis_distance
Make Clean Namesmake_clean_names
McNemar's Chi-squared Test for Count Datamcnemar_test pairwise_mcnemar_test
Exact Multinomial Testmultinom_test
Rounding and Formatting p-valuesp_adj_names p_detect p_format p_mark_significant p_names p_round
Proportion Testpairwise_prop_test prop_test row_wise_prop_test
Test for Trend in Proportionsprop_trend_test
Pull Lower and Upper Triangular Part of a Matrixpull_lower_triangle pull_triangle pull_upper_triangle
Remove Non-Significant from Statistical Testsremove_ns
Replace Lower and Upper Triangular Part of a Matrixreplace_lower_triangle replace_triangle replace_upper_triangle
Sample n Rows By Group From a Tablesample_n_by
Shapiro-Wilk Normality Testmshapiro_test shapiro_test
Sign Testpairwise_sign_test sign_test
T-testpairwise_t_test t_test
Tukey Honest Significant Differencestukey_hsd tukey_hsd.data.frame tukey_hsd.default tukey_hsd.lm
Welch One-Way ANOVA Testwelch_anova_test
Wilcoxon Effect Sizewilcox_effsize
Wilcoxon Testspairwise_wilcox_test wilcox_test