The Appropriateness of Outlier Exclusion Approaches Depends on the Expected Contamination: Commentary on André (2022)

Authors

Daniel Villanova, University of Arkansas, FayettevilleFollow

Document Type

Response or Comment

Publication Date

7-2023

Keywords

outliers; false positives; power; methodology; statistical analysis

Abstract

In a recent article, André (2022) addressed the decision to exclude outliers using a threshold across conditions or within conditions and offered a clear recommendation to avoid within-conditions exclusions because of the possibility for large false-positive inflation. In this commentary, I note that André’s simulations did not include the situation for which within-conditions exclusion has previously been recommended—when across-conditions exclusion would exacerbate selection bias. Examining test performance in this situation confirms the recommendation for within-conditions exclusion in such a circumstance. Critically, the suitability of exclusion criteria must be considered in relationship to assumptions about data-generating mechanisms.

Citation

Villanova, D. (2023). The Appropriateness of Outlier Exclusion Approaches Depends on the Expected Contamination: Commentary on André (2022). Advances in Methods and Practices in Psychological Science, 6 (3) https://doi.org/10.1177/25152459231186577

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License