Cohen's - a common effect size - contains a positive bias. The traditional bias correction, based on strict distribution assumption, does not always work for a small study with limited data. The non-parametric bootstrapping is not limited by distribution assumption and can be used to remove the bias in Cohen's . A real example is included to illustrate the implementation of bootstrap bias estimation and the removal of sizable bias in Cohen's .
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| http://dx.doi.org/10.1080/00221309.2023.2172545 | DOI Listing |
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