Dichotomizing continuous predictors in multiple regression: a bad idea

被引:1559
作者
Royston, P
Altman, DG
Sauerbrei, W
机构
[1] MRC, Clin Trials Unit, London NW1 2DA, England
[2] Univ Oxford, Ctr Stat Med, Wolfson Coll Annexe, Oxford OX2 6UD, England
[3] Univ Hosp Freiburg, Inst Med Biometry & Med Informat, D-79104 Freiburg, Germany
基金
英国医学研究理事会;
关键词
continuous covariates; dichotomization; categorization; regression; efficiency; clinical research;
D O I
10.1002/sim.2331
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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 (c) 2005 John Wiley & Sons, Ltd.
引用
收藏
页码:127 / 141
页数:15
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