R rstatix package
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.
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Add P-value Significance Symbols
Autocompute P-value Positions For Plotting Significance
Autocompute P-value Positions For Plotting Significance
Autocompute P-value Positions For Plotting Significance
Adjust P-values for Multiple Comparisons
Create Nice Summary Tables of ANOVA Results
Convert a Correlation Test Data Frame into a Correlation Matrix
Box's M-test for Homogeneity of Covariance Matrices
Chi-squared Test for Count Data
Chi-squared Test for Count Data
Compute Cohen's d Measure of Effect Size
Replace Correlation Coefficients by Symbols
Compute Correlation Matrix with P-values
Add Significance Levels To a Correlation Matrix
Compute Correlation Matrix with P-values
Visualize Correlation Matrix Using Base Plot
Compute Correlation Matrix with P-values
Reorder Correlation Matrix
Subset Correlation Matrix
Convert a Table of Counts into a Data Frame of cases
Extract Label Information from Statistical Tests
Arrange Rows by Column Values
Get User Specified Variable Names
Group a Data Frame by One or more Variables
Functions to Label Data Frames by Grouping Variables
Functions to Label Data Frames by Grouping Variables
Select Columns in a Data Frame
Split a Data Frame into Subset
Unite Multiple Columns into One
Unite Multiple Columns into One
Alternative to dplyr::do for Doing Anything
Dunn's Test of Multiple Comparisons
Pairwise Comparisons of Estimated Marginal Means
Chi-squared Test for Count Data
Build Factorial Designs for ANOVA
Fisher's Exact Test for Count Data
Friedman Test Effect Size (Kendall's W Value)
Games Howell Post-hoc Tests
Create a List of Possible Comparisons Between Groups
Pairwise Comparisons of Estimated Marginal Means
Extract Label Information from Statistical Tests
Compute Summary Statistics
Extract Label Information from Statistical Tests
Autocompute P-value Positions For Plotting Significance
Identify Univariate Outliers Using Boxplot Methods
Identify Univariate Outliers Using Boxplot Methods
Identify Univariate Outliers Using Boxplot Methods
Kruskal-Wallis Effect Size
Compute Mahalanobis Distance and Flag Multivariate Outliers
McNemar's Chi-squared Test for Count Data
Shapiro-Wilk Normality Test
Chi-squared Test for Count Data
Chi-squared Test for Count Data
Chi-squared Test for Count Data
Fisher's Exact Test for Count Data
McNemar's Chi-squared Test for Count Data
Chi-squared Test for Count Data
Test for Trend in Proportions
Pull Lower and Upper Triangular Part of a Matrix
Pull Lower and Upper Triangular Part of a Matrix
Pull Lower and Upper Triangular Part of a Matrix
Rounding and Formatting p-values
Rounding and Formatting p-values
Rounding and Formatting p-values
Rounding and Formatting p-values
Rounding and Formatting p-values
Rounding and Formatting p-values
Replace Lower and Upper Triangular Part of a Matrix
Replace Lower and Upper Triangular Part of a Matrix
Replace Lower and Upper Triangular Part of a Matrix
Fisher's Exact Test for Count Data
Sample n Rows By Group From a Table
Shapiro-Wilk Normality Test
Chi-squared Test for Count Data
Tukey Honest Significant Differences
Tukey Honest Significant Differences
Tukey Honest Significant Differences
Tukey Honest Significant Differences
