  Effect size indices are useful parameters that quantify the strength of
association and are unaffected by sample size. There are many available effect
size parameters and estimators, but it is difficult to compare effect sizes
across studies as most are defined for a specific type of population parameter.
We recently introduced a new Robust Effect Size Index (RESI) and confidence
interval, which is advantageous because it is not model-specific. Here we
present the RESI R package, which makes it easy to report the RESI and its
confidence interval for many different model classes, with a consistent
interpretation across parameters and model types. The package produces
coefficient, ANOVA tables, and overall Wald tests for model inputs, appending
the RESI estimate and confidence interval to each. The package also includes
functions for visualization and conversions to and from other effect size
measures. For illustration, we analyze and interpret three different model
types.
