The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Best Practices for Using Median Splits, Artificial Categorization, and their Continuous Alternatives
Open accessAbstract
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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Citations
Cites
Multiple regression: testing and interpreting interactions
(1992) · Choice Reviews Online · doi:10.5860/choice.29-3352 · Cited by 36,654
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Cohen, P., Cohen, P., West, S. G., & Aiken, L. S. (2014) · Psychology Press eBooks · doi:10.4324/9781410606266 · Cited by 20,737
Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences
Kemp, F. (2003) · Journal of the Royal Statistical Society: Series D (The Statistician) · doi:10.1046/j.1467-9884.2003.t01-2-00383_4.x · Cited by 9,293
Applied Linear Statistical Models
(1997) · Technometrics · doi:10.1080/00401706.1997.10485141 · Cited by 7,185
Agresti, A. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/0471249688 · Cited by 6,746
Simultaneous Statistical Inference
Miller, R. G. (1981) · Springer Series in Statistics · doi:10.1007/978-1-4613-8122-8 · Cited by 5,604
On the practice of dichotomization of quantitative variables.
MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D. (2002) · Psychological Methods · doi:10.1037/1082-989x.7.1.19 · Cited by 3,538
(2016) · Time Series with Mixed Spectra · doi:10.1201/b15154-8 · Cited by 2,739
Fiske, S. T., & Taylor, S. E. (1991) · Cited by 2,339
Cohen, J. (1983) · Applied Psychological Measurement · doi:10.1177/014662168300700301 · Cited by 1,564 · cited 2×
“The issues surrounding artificially categorizing naturally continuous variables were summarized and brought to the psychological literature by Cohen (1983), who concluded that the benefits of artificial categorization were not worth the costs in terms of statistical power and accuracy of the estimated relations.”
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Cited by
Hooper, L. M., Doehler, K., Jankowski, P. J., & Tomek, S. E. (2012) · The Family Journal · doi:10.1177/1066480711435320 · Cited by 60
Characterizing the ASD–ADHD phenotype: measurement structure and invariance in a clinical sample
Krakowski, A. D., Cost, K. T., Szatmari, P., Anagnostou, E., Crosbie, J., Schachar, R., Duku, E., Georgiades, S., Ayub, M., Kelley, E., et al. (2022) · Journal of Child Psychology and Psychiatry · doi:10.1111/jcpp.13609 · Cited by 26
Koutlas, A., Smilios, I., Kokkinou, E. M., Myrkos, A., Kounoupis, A., Dipla, K., & Zafeiridis, A. (2024) · Research Quarterly for Exercise and Sport · doi:10.1080/02701367.2022.2159309 · Cited by 18
Deák, Z., Vaznonienė, G., & Wojewódzka-Wiewiórska, A. (2024) · Serbian Journal of Management · doi:10.5937/sjm19-51118 · Cited by 5
Kapadi, R., Elander, J., & Bateman, A. H. (2024) · Substance Use & Misuse · doi:10.1080/10826084.2024.2320373 · Cited by 2
“Also, for the logistic regression analyses, the pain acceptance measures were dichotomized using median splits, which can be controversial and should be avoided where possible (DeCoster et al., 2011).”
Method
Metadata
- Authors
- DeCoster, J., Gallucci, M., & Iselin, A.-M. R.
- Venue
- Journal of Experimental Psychopathology
- Publisher
- SAGE Publications
- Published
- 2011-05
- Volume
- 2
- Issue
- 2
- Pages
- 197-209
- ISSN
- 2043-8087 (ISSN-L)
- OpenAlex
- W2171282425
- Cited by
- 367
- References
- 39
- FWCI
- 2.17
- Type
- journal article
- Language
- en
- Open access
- bronze
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- CoChat. (2026). Citation check: Best Practices for Using Median Splits, Artificial Categorization, and their Continuous Alternatives. https://app.cochat.ai/papers/10.5127/jep.008310
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- DeCoster, J., Gallucci, M., & Iselin, A.-M. R. (2011). Best Practices for Using Median Splits, Artificial Categorization, and their Continuous Alternatives. Journal of Experimental Psychopathology. https://doi.org/10.5127/jep.008310
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.