Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Study on the Power Comparison between Logistic Regression and Offset Poisson Regression for Binary Data

  • Kim, Dae-Youb (Department of Statistics, Hankuk University of Foreign Studies) ;
  • Park, Heung-Sun (Department of Statistics, Hankuk University of Foreign Studies)
  • Received : 2012.01.24
  • Accepted : 2012.06.03
  • Published : 2012.07.31
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Abstract

In this paper, for analyzing binary data, Poisson regression with offset and logistic regression are compared with respect to the power via simulations. Poisson distribution can be used as an approximation of binomial distribution when n is large and p is small; however, we investigate if the same conditions can be held for the power of significant tests between logistic regression and offset poisson regression. The result is that when offset size is large for rare events offset poisson regression has a similar power to logistic regression, but it has an acceptable power even with a moderate prevalence rate. However, with a small offset size (< 10), offset poisson regression should be used with caution for rare events or common events. These results would be good guidelines for users who want to use offset poisson regression models for binary data.

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