{
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  "Type": "Package",
  "Title": "Pipe-Friendly Framework for Basic Statistical Tests",
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  "Authors@R": "c(\nperson(\"Alboukadel\", \"Kassambara\", role = c(\"aut\", \"cre\"), email = \"alboukadel.kassambara@gmail.com\"))",
  "Description": "Provides a simple and intuitive pipe-friendly framework,\ncoherent with the 'tidyverse' design philosophy, for performing\nbasic statistical tests, including t-test, Wilcoxon test,\nANOVA, Kruskal-Wallis and correlation analyses. The output of\neach test is automatically transformed into a tidy data frame\nto facilitate visualization. Additional functions are available\nfor reshaping, reordering, manipulating and visualizing\ncorrelation matrix. Functions are also included to facilitate\nthe analysis of factorial experiments, including purely\n'within-Ss' designs (repeated measures), purely 'between-Ss'\ndesigns, and mixed 'within-and-between-Ss' designs. It's also\npossible to compute several effect size metrics, including \"eta\nsquared\" for ANOVA, \"Cohen's d\" for t-test and 'Cramer V' for\nthe association between categorical variables. The package\ncontains helper functions for identifying univariate and\nmultivariate outliers, assessing normality and homogeneity of\nvariances.",
  "License": "GPL-2",
  "Encoding": "UTF-8",
  "URL": "https://rpkgs.datanovia.com/rstatix/",
  "BugReports": "https://github.com/kassambara/rstatix/issues",
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  "Language": "en-US",
  "Config/pak/sysreqs": "cmake make libicu-dev",
  "Repository": "https://kassambara.r-universe.dev",
  "Date/Publication": "2025-10-20 10:08:21 UTC",
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    },
    {
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    },
    {
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    "add_significance",
    "add_x_position",
    "add_xy_position",
    "add_y_position",
    "adjust_pvalue",
    "Anova",
    "anova_summary",
    "anova_test",
    "as_cor_mat",
    "augment",
    "binom_test",
    "box_m",
    "chisq_descriptives",
    "chisq_test",
    "cochran_qtest",
    "cohens_d",
    "convert_as_factor",
    "cor_as_symbols",
    "cor_gather",
    "cor_get_pval",
    "cor_mark_significant",
    "cor_mat",
    "cor_plot",
    "cor_pmat",
    "cor_reorder",
    "cor_select",
    "cor_spread",
    "cor_test",
    "counts_to_cases",
    "cramer_v",
    "create_test_label",
    "desc",
    "df_arrange",
    "df_get_var_names",
    "df_group_by",
    "df_label_both",
    "df_label_value",
    "df_nest_by",
    "df_select",
    "df_split_by",
    "df_unite",
    "df_unite_factors",
    "doo",
    "drop_na",
    "dunn_test",
    "emmeans_test",
    "eta_squared",
    "expected_freq",
    "factorial_design",
    "filter",
    "fisher_test",
    "freq_table",
    "friedman_effsize",
    "friedman_test",
    "games_howell_test",
    "gather",
    "get_anova_table",
    "get_comparisons",
    "get_description",
    "get_emmeans",
    "get_mode",
    "get_n",
    "get_pwc_label",
    "get_summary_stats",
    "get_test_label",
    "get_y_position",
    "group_by",
    "identify_outliers",
    "is_extreme",
    "is_outlier",
    "kruskal_effsize",
    "kruskal_test",
    "levene_test",
    "mahalanobis_distance",
    "make_clean_names",
    "Manova",
    "mcnemar_test",
    "mshapiro_test",
    "multinom_test",
    "mutate",
    "observed_freq",
    "p_adj_names",
    "p_detect",
    "p_format",
    "p_mark_significant",
    "p_names",
    "p_round",
    "pairwise_binom_test",
    "pairwise_binom_test_against_p",
    "pairwise_chisq_gof_test",
    "pairwise_chisq_test_against_p",
    "pairwise_fisher_test",
    "pairwise_mcnemar_test",
    "pairwise_prop_test",
    "pairwise_sign_test",
    "pairwise_t_test",
    "pairwise_wilcox_test",
    "partial_eta_squared",
    "pearson_residuals",
    "prop_test",
    "prop_trend_test",
    "pull_lower_triangle",
    "pull_triangle",
    "pull_upper_triangle",
    "remove_ns",
    "reorder_levels",
    "replace_lower_triangle",
    "replace_triangle",
    "replace_upper_triangle",
    "row_wise_fisher_test",
    "row_wise_prop_test",
    "sample_n_by",
    "select",
    "set_ref_level",
    "shapiro_test",
    "sign_test",
    "spread",
    "std_residuals",
    "t_test",
    "tibble",
    "tidy",
    "tukey_hsd",
    "welch_anova_test",
    "wilcox_effsize",
    "wilcox_test"
  ],
  "_help": [
    {
      "page": "add_significance",
      "title": "Add P-value Significance Symbols",
      "topics": [
        "add_significance"
      ]
    },
    {
      "page": "adjust_pvalue",
      "title": "Adjust P-values for Multiple Comparisons",
      "topics": [
        "adjust_pvalue"
      ]
    },
    {
      "page": "anova_summary",
      "title": "Create Nice Summary Tables of ANOVA Results",
      "topics": [
        "anova_summary"
      ]
    },
    {
      "page": "anova_test",
      "title": "Anova Test",
      "topics": [
        "anova_test",
        "get_anova_table",
        "plot.anova_test",
        "print.anova_test"
      ]
    },
    {
      "page": "as_cor_mat",
      "title": "Convert a Correlation Test Data Frame into a Correlation Matrix",
      "topics": [
        "as_cor_mat"
      ]
    },
    {
      "page": "binom_test",
      "title": "Exact Binomial Test",
      "topics": [
        "binom_test",
        "pairwise_binom_test",
        "pairwise_binom_test_against_p"
      ]
    },
    {
      "page": "box_m",
      "title": "Box's M-test for Homogeneity of Covariance Matrices",
      "topics": [
        "box_m"
      ]
    },
    {
      "page": "chisq_test",
      "title": "Chi-squared Test for Count Data",
      "topics": [
        "chisq_descriptives",
        "chisq_test",
        "expected_freq",
        "observed_freq",
        "pairwise_chisq_gof_test",
        "pairwise_chisq_test_against_p",
        "pearson_residuals",
        "std_residuals"
      ]
    },
    {
      "page": "cochran_qtest",
      "title": "Cochran's Q Test",
      "topics": [
        "cochran_qtest"
      ]
    },
    {
      "page": "cohens_d",
      "title": "Compute Cohen's d Measure of Effect Size",
      "topics": [
        "cohens_d"
      ]
    },
    {
      "page": "factors",
      "title": "Factors",
      "topics": [
        "convert_as_factor",
        "reorder_levels",
        "set_ref_level"
      ]
    },
    {
      "page": "cor_as_symbols",
      "title": "Replace Correlation Coefficients by Symbols",
      "topics": [
        "cor_as_symbols"
      ]
    },
    {
      "page": "cor_reshape",
      "title": "Reshape Correlation Data",
      "topics": [
        "cor_gather",
        "cor_spread"
      ]
    },
    {
      "page": "cor_mark_significant",
      "title": "Add Significance Levels To a Correlation Matrix",
      "topics": [
        "cor_mark_significant"
      ]
    },
    {
      "page": "cor_mat",
      "title": "Compute Correlation Matrix with P-values",
      "topics": [
        "cor_get_pval",
        "cor_mat",
        "cor_pmat"
      ]
    },
    {
      "page": "cor_plot",
      "title": "Visualize Correlation Matrix Using Base Plot",
      "topics": [
        "cor_plot"
      ]
    },
    {
      "page": "cor_reorder",
      "title": "Reorder Correlation Matrix",
      "topics": [
        "cor_reorder"
      ]
    },
    {
      "page": "cor_select",
      "title": "Subset Correlation Matrix",
      "topics": [
        "cor_select"
      ]
    },
    {
      "page": "cor_test",
      "title": "Correlation Test",
      "topics": [
        "cor_test"
      ]
    },
    {
      "page": "counts_to_cases",
      "title": "Convert a Table of Counts into a Data Frame of cases",
      "topics": [
        "counts_to_cases"
      ]
    },
    {
      "page": "cramer_v",
      "title": "Compute Cramer's V",
      "topics": [
        "cramer_v"
      ]
    },
    {
      "page": "df_arrange",
      "title": "Arrange Rows by Column Values",
      "topics": [
        "df_arrange"
      ]
    },
    {
      "page": "df_get_var_names",
      "title": "Get User Specified Variable Names",
      "topics": [
        "df_get_var_names"
      ]
    },
    {
      "page": "df_group_by",
      "title": "Group a Data Frame by One or more Variables",
      "topics": [
        "df_group_by"
      ]
    },
    {
      "page": "df_label_value",
      "title": "Functions to Label Data Frames by Grouping Variables",
      "topics": [
        "df_label_both",
        "df_label_value"
      ]
    },
    {
      "page": "df_nest_by",
      "title": "Nest a Tibble By Groups",
      "topics": [
        "df_nest_by"
      ]
    },
    {
      "page": "df_select",
      "title": "Select Columns in a Data Frame",
      "topics": [
        "df_select"
      ]
    },
    {
      "page": "df_split_by",
      "title": "Split a Data Frame into Subset",
      "topics": [
        "df_split_by"
      ]
    },
    {
      "page": "df_unite",
      "title": "Unite Multiple Columns into One",
      "topics": [
        "df_unite",
        "df_unite_factors"
      ]
    },
    {
      "page": "doo",
      "title": "Alternative to dplyr::do for Doing Anything",
      "topics": [
        "doo"
      ]
    },
    {
      "page": "dunn_test",
      "title": "Dunn's Test of Multiple Comparisons",
      "topics": [
        "dunn_test"
      ]
    },
    {
      "page": "emmeans_test",
      "title": "Pairwise Comparisons of Estimated Marginal Means",
      "topics": [
        "emmeans_test",
        "get_emmeans"
      ]
    },
    {
      "page": "eta_squared",
      "title": "Effect Size for ANOVA",
      "topics": [
        "eta_squared",
        "partial_eta_squared"
      ]
    },
    {
      "page": "factorial_design",
      "title": "Build Factorial Designs for ANOVA",
      "topics": [
        "factorial_design"
      ]
    },
    {
      "page": "fisher_test",
      "title": "Fisher's Exact Test for Count Data",
      "topics": [
        "fisher_test",
        "pairwise_fisher_test",
        "row_wise_fisher_test"
      ]
    },
    {
      "page": "freq_table",
      "title": "Compute Frequency Table",
      "topics": [
        "freq_table"
      ]
    },
    {
      "page": "friedman_effsize",
      "title": "Friedman Test Effect Size (Kendall's W Value)",
      "topics": [
        "friedman_effsize"
      ]
    },
    {
      "page": "friedman_test",
      "title": "Friedman Rank Sum Test",
      "topics": [
        "friedman_test"
      ]
    },
    {
      "page": "games_howell_test",
      "title": "Games Howell Post-hoc Tests",
      "topics": [
        "games_howell_test"
      ]
    },
    {
      "page": "get_comparisons",
      "title": "Create a List of Possible Comparisons Between Groups",
      "topics": [
        "get_comparisons"
      ]
    },
    {
      "page": "get_mode",
      "title": "Compute Mode",
      "topics": [
        "get_mode"
      ]
    },
    {
      "page": "get_test_label",
      "title": "Extract Label Information from Statistical Tests",
      "topics": [
        "create_test_label",
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