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May 1, 2011Journal of Experimental Psychopathology361 citationsOpen Access

Best Practices for Using Median Splits, Artificial Categorization, and their Continuous Alternatives

JDJamie DeCosterMGMarcello GallucciAIAnne‐Marie R. Iselin

Key Points

  • Provide practical methodological guidance on the costs, justifications, and continuous alternatives to artificial categorization and median splits in experimental psychopathology.
  • Reviewed theoretical and practical arguments surrounding the transformation of continuous variables into categorical variables.
  • Synthesized statistical frameworks to assess when artificial categorization is justifiable versus when continuous models should be used.
  • Identifies specific circumstances where artificial categorization compromises statistical power and effect size estimation.
  • Outlines recommendations for justifying categorization and provides practical frameworks for implementing continuous statistical alternatives.

Abstract

Methodologists have long discussed the costs and benefits of using medians or other cut points to artificially turn continuous variables into categorical variables. The current paper attempts to provide a perspective on this literature that will be of practical use to experimental psychopathologists. After discussing the reasons that clinical researchers might use artificial categorization, we summarize the arguments both for and against this procedure. We then provide a number of specific suggestions related to the use of artificial categorization, including our thoughts on when researchers should use artificial categories, how their use can be justified, what continuous alternatives are available, and how the continuous alternatives should be used.

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Cite This Study

DeCoster et al. (2011) studied this question.

synapsesocial.com/papers/69db04420d8d6ef495a3cab7https://doi.org/10.5127/jep.008310
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