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Stat Med. 2006 Jan 15;25(1):127-41.

Dichotomizing continuous predictors in multiple regression: a bad idea.

Author information

  • 1MRC Clinical Trials Unit, 222 Euston Road, London NW1 2DA, UK. patrick.royston@ctu.mrc.ac.uk

Abstract

In medical research, continuous variables are often converted into categorical variables by grouping values into two or more categories. We consider in detail issues pertaining to creating just two groups, a common approach in clinical research. We argue that the simplicity achieved is gained at a cost; dichotomization may create rather than avoid problems, notably a considerable loss of power and residual confounding. In addition, the use of a data-derived 'optimal' cutpoint leads to serious bias. We illustrate the impact of dichotomization of continuous predictor variables using as a detailed case study a randomized trial in primary biliary cirrhosis. Dichotomization of continuous data is unnecessary for statistical analysis and in particular should not be applied to explanatory variables in regression models.

Copyright 2005 John Wiley & Sons, Ltd.

PMID:
16217841
[PubMed - indexed for MEDLINE]
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