In both theoretical and applied research, it is often of interest to assess the strength of an observed association. This is typically done to allow the judgment of the magnitude of an effect, especially when units of measurement are not meaningful. Though some indices of effect size, such as the correlation coefficient (itself a standardized covariance coefficient) are readily available, other measures are often harder to obtain.
effectsize fills this important gap, providing utilities for easily
estimating a wide variety of standardized effect sizes (i.e., effect sizes
that are not tied to the units of measurement of the variables of interest)
and their confidence intervals (CIs), from a variety of statistical models
and hypothesis tests, such as
References: Ben-Shachar et al. (2020) doi: 10.21105/joss.02815.
Ken Kelley [contributor]
David Stanley [contributor]
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