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RESI

RESI is an R package designed to implement the Robust Effect Size Index (RESI, denoted as S) described in Vandekar, Tao, & Blume (2020). The RESI is a versatile effect size measure that can be easily computed and added to common reports (such as summary and ANOVA tables). This package currently supports lm, glm, nls, survreg, coxph, hurdle, zeroinfl, gee, geeglm, lme, lmerMod, lmrob, and glmrob models. Confidence intervals are now computed using the bootstrap or one of three asymptotic methods: a profiled quadratic form, Cornish-Fisher expansion, or normal approximation. A Bayesian bootstrap is also available for lm and nls models. In addition to the main resi function, the package also includes a point-estimate-only function (resi_pe), conversions from S to other common effect size measures and vice versa, print methods, plot methods, summary methods, and Anova/anova methods.

If you would like to contribute to the package, please branch off of our GitHub and submit a pull request describing the contribution. Please use the GitHub Issues page to report any problems and the Discussions page to seek additional support.

References

Jones M, Kang K, Vandekar S (2025). RESI: An R Package for Robust Effect Sizes. Journal of Statistical Software, 112(3), 1–27. https://doi.org/10.18637/jss.v112.i03.

Kang K, Jones MT, Armstrong K, Avery S, McHugo M, Heckers S, & Vandekar S. Accurate Confidence and Bayesian Interval Estimation for Non-centrality Parameters and Effect Size Indices. Psychometrika. 2023. https://doi.org/10.1007/s11336-022-09899-x.

Kang K, Seidlitz J, Bethlehem RAI, et al. Study design features increase replicability in brain-wide association studies. Nature. 2024. https://doi.org/10.1038/s41586-024-08260-9.

Vandekar S, Tao R, Blume J. A Robust Effect Size Index. Psychometrika. 2020;85(1):232–246. https://doi.org/10.1007/s11336-020-09698-2.

Zhang X, Muscatello R, Jones M, Corbett B, Vandekar S. Asymptotic Distribution of Robust Effect Size Index. arXiv:2601.19004. 2026. https://doi.org/10.48550/arXiv.2601.19004.

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Version

Install

install.packages('RESI')

Monthly Downloads

354

Version

1.5.1

License

GPL-3

Issues

Pull Requests

Stars

Forks

Maintainer

Simon Vandekar

Last Published

August 21st, 2026

Functions in RESI (1.5.1)

simCalibrationSim

Asymptotic Calibration Check for RESI Variance Estimates
d2S

Covert Cohen's d to |S|
S2fsq

Covert S to Cohen's f^2
anova.resi

Anova method for resi objects
S2chisq

Convert non-zero S to Chi-square statistic
S2d

Convert S to Cohen's d
Rsq2S

Covert R^2 to S
S2z

Convert RESI (S) estimate to Z statistic
chisq2S

Compute the robust effect size index estimate from chi-squared statistic.
S2Rsq

Covert S to R^2
depression

Depression Treatment Data
resi_pe

Robust Effect Size Index (RESI) Point Estimation
fsq2S

Covert Cohen's f^2 to S
resi_pe_asymptotic

Robust Effect Size Index with Asymptotic Confidence Intervals
plot.resi

Plotting RESI Estimates and CIs
omnibus

Omnibus (Overall) Wald Test for resi objects
f2S

Compute the robust effect size index estimate from F-statistic
insurancePlasmodeSim

Insurance Plasmode Simulation for RESI Evaluation
resi

Robust Effect Size Index (RESI) point and interval estimation for models
ggplot.resi

Plotting RESI Estimates and CIs
insurance

US Health Insurance Data
t2S

Compute the robust effect size index estimate from t statistic (default)
summary.resi

Summary method for resi objects
z2S

Compute the robust effect size index estimate from Z statistic
simCompareMethodsFigures

Per-Term CI Method Comparison Figures
simRecomputeSummary

Recompute Summary Table from Raw Simulation Output
simEstimatorFigures

Estimator Comparison Figures: t2S/f2S vs z2S/chisq2S
simFigures

Simulation Performance Figures for RESI Evaluation
simCalibrationFigures

Calibration Figures for RESI Variance Estimates