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Logistic regression analysis for more than one characteristic of exposure
B McKnight1, L S Cook, N S Weiss
1Department of Biostatistics, University of Washington, and Fred Hutchinson Cancer Research Center, Seattle 98195-7232, USA.
Abstract:
When more than one characteristic of an exposure is under study, it is easy to misinterpret the results of a logistic regression analysis that incorporates terms for each characteristic. For example, in a study of the risk of endometrial cancer in relation to the duration and the recency of use of estrogen replacement therapy (ERT), simultaneously including terms for duration and recency of exposure to ERT in a logistic model may leave the mistaken impression that it is possible to adjust for recency when a given duration of ERT use is compared with no use. In this article, the authors show why such an adjusted comparison is impossible, and they discuss several pitfalls in the interpretation of logistic regression coefficients when two or more characteristics of exposure are under study. They also suggest a method for avoiding these pitfalls.
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