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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.
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
