Negative Consequences of Dichotomizing Continuous Predictor Variables

Marketing researchers frequently split (dichotomize) continuous predictor variables into two groups, such as with a median split, before performing data analysis. The practice is prevalent but its effects are not well understood. In this paper, we present historic results on the effects of dichotomization of normal predictor variables rederived in a regression context that may be more relevant to marketing researchers. Then, we present new results on the effect of dichotomizing continuous predictor variables having a variety of non-normal distributions and examine the effects of dichotomization on model specification and fit in multiple regression. We conclude that dichotomization has only negative consequences and should be avoided