Package index • effectsize

Indices of Effect Size
`effectsize()`	Effect Sizes
Standardized differences Effect sizes for comparing two groups
`cohens_d()` `hedges_g()` `glass_delta()`	Cohen's d and Other Standardized Differences
`repeated_measures_d()` `rm_d()`	Standardized Mean Differences for Repeated Measures
`mahalanobis_d()`	Mahalanobis' D (a multivariate Cohen's d)
`rank_biserial()` `cliffs_delta()`	Dominance Effect Sizes for Rank Based Differences
`p_superiority()` `cohens_u1()` `cohens_u2()` `cohens_u3()` `p_overlap()` `vd_a()` `wmw_odds()`	Cohen's Us and Other Common Language Effect Sizes (CLES)
`means_ratio()`	Ratio of Means
For contingency tables Effect sizes for categorical outcomes
`phi()` `cramers_v()` `tschuprows_t()` `cohens_w()` `fei()` `pearsons_c()`	\(\phi\) and Other Contingency Tables Correlations
`oddsratio()` `riskratio()` `cohens_h()` `arr()` `nnt()`	Odds Ratios, Risk Ratios and Other Effect Sizes for 2-by-2 Contingency Tables
`cohens_g()`	Effect Size for Paired Contingency Tables
Comparing multiple groups Effect sizes for ANOVA
`eta_squared()` `omega_squared()` `epsilon_squared()` `cohens_f()` `cohens_f_squared()` `eta_squared_posterior()`	\(\eta^2\) and Other Effect Size for ANOVA
`rank_epsilon_squared()` `rank_eta_squared()` `kendalls_w()`	Effect Size for Rank Based ANOVA
Standardized parameters Functions from other packages relating to parameter standardization and perdictor dominance
`standardize_parameters()` `standardize_posteriors()`	Parameters standardization (from parameters)
`standardize(<default>)`	Re-fit a model with standardized data (from datawizard)
`standardize_info()`	Get Standardization Information (from parameters)
`dominance_analysis()`	Dominance Analysis (from parameters)
`r2_semipartial()`	Semi-Partial (Part) Correlation Squared (\(\Delta R^2\))
Correlations Correlations are a standardized effect size of association
`correlation()`	Correlation Analysis (from correlation)
`cor_test()`	Correlation test (from correlation)
Effect Size Conversion
From Test Statistics Extract approximate effect sizes from their commonly associated test statistics
`t_to_d()` `z_to_d()` `F_to_d()` `t_to_r()` `z_to_r()` `F_to_r()`	Convert t, z, and F to Cohen's d or partial-r
`F_to_eta2()` `t_to_eta2()` `F_to_epsilon2()` `t_to_epsilon2()` `F_to_eta2_adj()` `t_to_eta2_adj()` `F_to_omega2()` `t_to_omega2()` `F_to_f()` `t_to_f()` `F_to_f2()` `t_to_f2()`	Convert F and t Statistics to partial-\(\eta^2\) and Other ANOVA Effect Sizes
`chisq_to_phi()` `chisq_to_cohens_w()` `chisq_to_cramers_v()` `chisq_to_tschuprows_t()` `chisq_to_fei()` `chisq_to_pearsons_c()` `phi_to_chisq()`	Convert \(\chi^2\) to \(\phi\) and Other Correlation-like Effect Sizes
Between Effect Sizes Approximate effect sizes by converting between other related effect sizes
`d_to_r()` `r_to_d()` `oddsratio_to_d()` `logoddsratio_to_d()` `d_to_oddsratio()` `d_to_logoddsratio()` `oddsratio_to_r()` `logoddsratio_to_r()` `r_to_oddsratio()` `r_to_logoddsratio()`	Convert Between d, r, and Odds Ratio
`oddsratio_to_riskratio()` `oddsratio_to_arr()` `oddsratio_to_nnt()` `logoddsratio_to_riskratio()` `logoddsratio_to_arr()` `logoddsratio_to_nnt()` `riskratio_to_oddsratio()` `riskratio_to_arr()` `riskratio_to_logoddsratio()` `riskratio_to_nnt()` `arr_to_riskratio()` `arr_to_oddsratio()` `arr_to_logoddsratio()` `arr_to_nnt()` `nnt_to_oddsratio()` `nnt_to_logoddsratio()` `nnt_to_riskratio()` `nnt_to_arr()`	Convert Between Odds Ratios, Risk Ratios and Other Metrics of Change in Probabilities
`d_to_p_superiority()` `rb_to_p_superiority()` `rb_to_vda()` `d_to_u2()` `d_to_u1()` `d_to_u3()` `d_to_overlap()` `rb_to_wmw_odds()`	Convert Standardized Differences to Common Language Effect Sizes
`eta2_to_f2()` `eta2_to_f()` `f2_to_eta2()` `f_to_eta2()`	Convert Between ANOVA Effect Sizes
`odds_to_probs()` `probs_to_odds()`	Convert Between Odds and Probabilities
`w_to_fei()` `w_to_v()` `w_to_t()` `w_to_c()` `fei_to_w()` `v_to_w()` `t_to_w()` `c_to_w()` `v_to_t()` `t_to_v()`	Convert Between Effect Sizes for Contingency Tables Correlations
Interpretation
`equivalence_test(<effectsize_table>)`	Test Effect Size for Practical Equivalence to the Null
`interpret()`	Generic Function for Interpretation
`rules()` `is.rules()`	Create an Interpretation Grid
`interpret_bf()`	Interpret Bayes Factor (BF)
`interpret_cohens_d()` `interpret_hedges_g()` `interpret_glass_delta()`	Interpret Standardized Differences
`interpret_cohens_g()`	Interpret Cohen's g
`interpret_direction()`	Interpret Direction
`interpret_ess()` `interpret_rhat()`	Interpret Bayesian Diagnostic Indices
`interpret_gfi()` `interpret_agfi()` `interpret_nfi()` `interpret_nnfi()` `interpret_cfi()` `interpret_rfi()` `interpret_ifi()` `interpret_pnfi()` `interpret_rmsea()` `interpret_srmr()` `interpret(<lavaan>)` `interpret(<performance_lavaan>)`	Interpret of CFA / SEM Indices of Goodness of Fit
`interpret_icc()`	Interpret Intraclass Correlation Coefficient (ICC)
`interpret_kendalls_w()`	Interpret Kendall's Coefficient of Concordance W
`interpret_oddsratio()`	Interpret Odds Ratio
`interpret_omega_squared()` `interpret_eta_squared()` `interpret_epsilon_squared()` `interpret_r2_semipartial()`	Interpret ANOVA Effect Sizes
`interpret_p()`	Interpret p-Values
`interpret_pd()`	Interpret Probability of Direction (pd)
`interpret_r()` `interpret_phi()` `interpret_cramers_v()` `interpret_rank_biserial()` `interpret_fei()`	Interpret Correlation Coefficient
`interpret_r2()`	Interpret Coefficient of Determination (\(R^2\))
`interpret_rope()`	Interpret Bayesian Posterior Percentage in ROPE.
`interpret_vif()`	Interpret the Variance Inflation Factor (VIF)
Miscellaneous
`sd_pooled()` `mad_pooled()` `cov_pooled()`	Pooled Indices of (Co)Deviation
`is_effectsize_name()` `get_effectsize_name()` `get_effectsize_label()`	Checks for a Valid Effect Size Name
`format_standardize()`	Format a Standardized Vector
`plot(<effectsize_table>)` `print(<effectsize_table>)` `print_md(<effectsize_table>)` `print_html(<effectsize_table>)` `format(<effectsize_table>)` `print(<effectsize_difference>)`	Methods for effectsize Tables
Datasets
`hardlyworking`	Workers' Salary and Other Information
`rouder2016`	Jeff Rouder's Example Dataset for Repeated Measures
`screening_test`	Results from 2 Screening Tests
`RCT_table`	Fictional Results from a Workers' Randomized Control Trial
`Music_preferences`	Music Preference by College Major
`Music_preferences2`	Music Preference by College Major
`Smoking_FASD`	Frequency of FASD for Smoking Mothers
`food_class`	Classification of Foods
Extra Docs
`.es_aov_simple()` `.es_aov_strata()` `.es_aov_table()`	`effectsize` API
`effectsize_options`	`effectsize` options

Reference

Indices of Effect Size

Standardized differences

For contingency tables

Comparing multiple groups

Standardized parameters

Correlations

Effect Size Conversion

From Test Statistics

Between Effect Sizes

Interpretation

Miscellaneous

Datasets

Extra Docs