Reconciling questions about dichotomizing variables in criminal justice research

• We address unresolved questions about dichotomization in criminal justice research.
• Using continuous variables is a better alternative to dichotomization.
• This is true with non-normal distributions and when testing non-linear relations.
• It is also true when probing interaction effects and theorizing about subgroups.

PurposeDespite accumulating evidence against the practice of artificial dichotomization, its continued use among criminal justice researchers indicates that there are still unresolved questions about its appropriateness. Farrington and Loeber (2000) provided a discussion of how these issues impact research on delinquency, and many researchers have cited their article as a justification for dichotomization within the field of criminal justice. In the current study, we examine the reasons why researchers have cited Farrington and Loeber as a mechanism for answering some unresolved questions about whether and when dichotomization may be justified.MethodsWe used a forward citation search in PsycInfo to locate all articles citing Farrington and Loeber (2000) in support of dichotomization.ResultsThis search identified 126 articles which provided a total of 191 reasons supporting dichotomization. We explore these reasons, discussing whether they are consistent with evidence from simulation-based analyses and whether they are supported by existing statistical and methodological theory.ConclusionsDespite the large number of reasons for dichotomization provided by authors, we found very few that had empirical or theoretical support.