Pipe-Friendly Framework for Basic Statistical Tests

Documentation for package ‘rstatix’ version 0.7.2

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-- A --

add_significance	Add P-value Significance Symbols
add_xy_position	Autocompute P-value Positions For Plotting Significance
add_x_position	Autocompute P-value Positions For Plotting Significance
add_y_position	Autocompute P-value Positions For Plotting Significance
adjust_pvalue	Adjust P-values for Multiple Comparisons
anova_summary	Create Nice Summary Tables of ANOVA Results
anova_test	Anova Test
as_cor_mat	Convert a Correlation Test Data Frame into a Correlation Matrix

-- B --

binom_test	Exact Binomial Test
box_m	Box's M-test for Homogeneity of Covariance Matrices

-- C --

chisq_descriptives	Chi-squared Test for Count Data
chisq_test	Chi-squared Test for Count Data
cochran_qtest	Cochran's Q Test
cohens_d	Compute Cohen's d Measure of Effect Size
convert_as_factor	Factors
cor_as_symbols	Replace Correlation Coefficients by Symbols
cor_gather	Reshape Correlation Data
cor_get_pval	Compute Correlation Matrix with P-values
cor_mark_significant	Add Significance Levels To a Correlation Matrix
cor_mat	Compute Correlation Matrix with P-values
cor_plot	Visualize Correlation Matrix Using Base Plot
cor_pmat	Compute Correlation Matrix with P-values
cor_reorder	Reorder Correlation Matrix
cor_select	Subset Correlation Matrix
cor_spread	Reshape Correlation Data
cor_test	Correlation Test
counts_to_cases	Convert a Table of Counts into a Data Frame of cases
cramer_v	Compute Cramer's V
create_test_label	Extract Label Information from Statistical Tests

-- D --

df_arrange	Arrange Rows by Column Values
df_get_var_names	Get User Specified Variable Names
df_group_by	Group a Data Frame by One or more Variables
df_label_both	Functions to Label Data Frames by Grouping Variables
df_label_value	Functions to Label Data Frames by Grouping Variables
df_nest_by	Nest a Tibble By Groups
df_select	Select Columns in a Data Frame
df_split_by	Split a Data Frame into Subset
df_unite	Unite Multiple Columns into One
df_unite_factors	Unite Multiple Columns into One
doo	Alternative to dplyr::do for Doing Anything
dunn_test	Dunn's Test of Multiple Comparisons

-- E --

emmeans_test	Pairwise Comparisons of Estimated Marginal Means
eta_squared	Effect Size for ANOVA
expected_freq	Chi-squared Test for Count Data

-- F --

factorial_design	Build Factorial Designs for ANOVA
fisher_test	Fisher's Exact Test for Count Data
freq_table	Compute Frequency Table
friedman_effsize	Friedman Test Effect Size (Kendall's W Value)
friedman_test	Friedman Rank Sum Test

-- G --

games_howell_test	Games Howell Post-hoc Tests
get_anova_table	Anova Test
get_comparisons	Create a List of Possible Comparisons Between Groups
get_description	Extract Label Information from Statistical Tests
get_emmeans	Pairwise Comparisons of Estimated Marginal Means
get_mode	Compute Mode
get_n	Extract Label Information from Statistical Tests
get_pwc_label	Extract Label Information from Statistical Tests
get_summary_stats	Compute Summary Statistics
get_test_label	Extract Label Information from Statistical Tests
get_y_position	Autocompute P-value Positions For Plotting Significance

-- I --

identify_outliers	Identify Univariate Outliers Using Boxplot Methods
is_extreme	Identify Univariate Outliers Using Boxplot Methods
is_outlier	Identify Univariate Outliers Using Boxplot Methods

-- K --

kruskal_effsize	Kruskal-Wallis Effect Size
kruskal_test	Kruskal-Wallis Test

-- L --

Levene's Test

-- M --

mahalanobis_distance	Compute Mahalanobis Distance and Flag Multivariate Outliers
make_clean_names	Make Clean Names
mcnemar_test	McNemar's Chi-squared Test for Count Data
mshapiro_test	Shapiro-Wilk Normality Test
multinom_test	Exact Multinomial Test

-- O --

Chi-squared Test for Count Data

-- P --

pairwise_binom_test	Exact Binomial Test
pairwise_binom_test_against_p	Exact Binomial Test
pairwise_chisq_gof_test	Chi-squared Test for Count Data
pairwise_chisq_test_against_p	Chi-squared Test for Count Data
pairwise_fisher_test	Fisher's Exact Test for Count Data
pairwise_mcnemar_test	McNemar's Chi-squared Test for Count Data
pairwise_prop_test	Proportion Test
pairwise_sign_test	Sign Test
pairwise_t_test	T-test
pairwise_wilcox_test	Wilcoxon Tests
partial_eta_squared	Effect Size for ANOVA
pearson_residuals	Chi-squared Test for Count Data
plot.anova_test	Anova Test
print.anova_test	Anova Test
prop_test	Proportion Test
prop_trend_test	Test for Trend in Proportions
pull_lower_triangle	Pull Lower and Upper Triangular Part of a Matrix
pull_triangle	Pull Lower and Upper Triangular Part of a Matrix
pull_upper_triangle	Pull Lower and Upper Triangular Part of a Matrix
p_adj_names	Rounding and Formatting p-values
p_detect	Rounding and Formatting p-values
p_format	Rounding and Formatting p-values
p_mark_significant	Rounding and Formatting p-values
p_names	Rounding and Formatting p-values
p_round	Rounding and Formatting p-values

-- R --

remove_ns	Remove Non-Significant from Statistical Tests
reorder_levels	Factors
replace_lower_triangle	Replace Lower and Upper Triangular Part of a Matrix
replace_triangle	Replace Lower and Upper Triangular Part of a Matrix
replace_upper_triangle	Replace Lower and Upper Triangular Part of a Matrix
row_wise_fisher_test	Fisher's Exact Test for Count Data
row_wise_prop_test	Proportion Test

-- S --

sample_n_by	Sample n Rows By Group From a Table
set_ref_level	Factors
shapiro_test	Shapiro-Wilk Normality Test
sign_test	Sign Test
std_residuals	Chi-squared Test for Count Data

-- T --

tukey_hsd	Tukey Honest Significant Differences
tukey_hsd.data.frame	Tukey Honest Significant Differences
tukey_hsd.default	Tukey Honest Significant Differences
tukey_hsd.lm	Tukey Honest Significant Differences
t_test	T-test

-- W --