Toward a more nuanced understanding of the statistical properties of a median split

Dawn Iacobucci, Steven S. Posavac, Frank R. Kardes, Matthew J. Schneider, Deidre L. Popovich

Research output: Contribution to journalArticlepeer-review

141 Scopus citations

Abstract

Some behavioral researchers occasionally wish to conduct a median split on a continuous variable and use the result in subsequent modeling to facilitate analytic ease and communication clarity. Traditionally, this practice of dichotomization has been criticized for the resulting loss of information and reduction in power. More recently, this practice has been criticized for sometimes producing Type I errors for effects regarding other terms in a model, resulting in a recommendation of the unconditional avoidance of median splits. In this paper, we use simulation studies to demonstrate more thoroughly than has been shown in the literature to date when median splits should not be used, and conversely, to provide nuance and balance to the extant literature regarding when median splits may be used with complete analytical integrity. For the scenario we explicate, the use of a median split is as good as a continuous variable. Accordingly, there is no reason to outright reject median splits, and oftentimes the median split may be preferred as more parsimonious.

Original languageEnglish
Pages (from-to)652-665
Number of pages14
JournalJournal of Consumer Psychology
Volume25
Issue number4
DOIs
StatePublished - Oct 1 2015

Keywords

  • Categorization
  • Dichotomization
  • Median split
  • Median-split

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