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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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Background
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“We therefore used BDI as a dichotomous rather than continuous variable in our analyses (however, for a critical discussion see [33]).”
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“…this statistical technique reduces individual variability by placing individuals into groups (Altman and Royston 2006; Irwin and McClelland 2003; MacCallum et al. 2002) we consider the use these analyses in our study legitimate because the groupings were not arbitrary but based on empirically…”
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“Second, our analytical approach (categorizing continuous variables) was based on arbitrary cut-offs and may have resulted in loss of statistical power and increased probability of committing type-I errors (MacCallum et al. 2002).”
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“As for the correlations, brooding scores were correlated with the emotional disengagement score only in the high brooding group (n = 18), but not across all participants (n = 34) (see Fig. 3). This dichotomization of a quantitative measure is usually discouraged because it reduces the power or, on the other hand, over…”
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“Since the distribution of PREM dimension scores were skewed toward higher values, these variables were dichotomized [41].”
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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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