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On the practice of dichotomization of quantitative variables.

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MacCallum, Robert C., Zhang, Shaobo, Preacher, Kristopher J., Rucker, Derek D.·2002·Psychological Methods

DOI 10.1037/1082-989x.7.1.19

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Abstract

The authors examine the practice of dichotomization of quantitative measures, wherein relationships among variables are examined after 1 or more variables have been converted to dichotomous variables by splitting the sample at some point on the scale(s) of measurement. A common form of dichotomization is the median split, where the independent variable is split at the median to form high and low groups, which are then compared with respect to their means on the dependent variable. The consequences of dichotomization for measurement and statistical analyses are illustrated and discussed. The use of dichotomization in practice is described, and justifications that are offered for such usage are examined. The authors present the case that dichotomization is rarely defensible and often will yield misleading results.

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“The EMA-approved intermediate end points of reductions in total alcohol consumption and heavy drinking days are continuous measures and provide more statistical power to detect treatment effects than binary outcomes such as abstinence or no heavy drinking days (MacCallum et al., 2002; Yoo, 2010).”
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“Because categorizing quantitative variables may be criticized for several reasons (Maxwell and Delaney 1993; McCallum et al. 2002), we also tested the robustness of our results by using two different cutoff points for our firm size variable (up to 50 and up to 100 employees).”
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“Much of the variability along this continuum might represent measurement error around the mean scores of socially phobic and normally shy individuals, thereby reducing statistical power and increasing the likelihood that important effects will be missed (Cohen, 1983; MacCallum et al., 2002).”
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“based on median or tertile split), since post hoc splits are statistically inferior to continuous analyses in virtually all respects [17].”
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“The correlations for each level of the median split only have descriptive value (see MacCallum, Zhang, Preacher, & Rucker, 2002 ).”
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Authors: MacCallum, R. C., Zhang, S., Preacher, K. J., & Rucker, D. D.
Affiliations: The Ohio State University (US)
ORCID: Zhang, Shaobo
Preacher, Kristopher J.
Rucker, Derek D.
Venue: Psychological Methods
Publisher: American Psychological Association (APA)
Published: 2002
Volume: 7
Issue: 1
Pages: 19-40
ISSN: 1082-989X (ISSN-L)
1939-1463
DOI: 10.1037/1082-989x.7.1.19
OpenAlex: W2108096958
Semantic Scholar: 67646d3def337c40bbfa2476f0f1ff785ae18242
Cited by: 3,538
References: 42
Citations by year: 2026: 282 · 2025: 170 · 2024: 149 · 2023: 134 · 2022: 183 · 2021: 211 · 2020: 204 · 2019: 179 · 2018: 180 · 2017: 223 · 2016: 208 · 2015: 208 · 2014: 184 · 2013: 187 · 2012: 138
FWCI: 55.97
Type: journal article
Language: en
Open access: green
kuscholarworks.ku.edu
Licence: other-oa
Locations: Psychological Methods (publishedVersion)
PubMed (publishedVersion)
KU ScholarWorks (The University of Kansas) (submittedVersion, other-oa)
Topics: Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: dichotomization, quantitative variables, statistical analysis, change of variables, measurement error
MeSH terms: Humans, Models, Psychological, Psychology

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On the practice of dichotomization of quantitative variables.

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