Abstract #301546

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JSM 2003 Abstract #301546
Activity Number: 128
Type: Contributed
Date/Time: Monday, August 4, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #301546
Title: Comparisons of Poisson Regression and Permutation T-test
Author(s): Mohammad A. Rahman*+ and Lin Stan and Mohammad F. Huque
Companies: Food and Drug Administration and Food and Drug Administration and Food and Drug Administration
Address: 20335 Swallow Point Rd., Gaithersburg, MD, 20886-1143,
Keywords: count data ; Poisson regression ; permutation test ; overdispersion
Abstract:

Often clinical trials result in count data of some kind. Examples include treatment trials for digital ulcers, acne, etc. A Poisson regression is sometimes proposed for the statistical analysis of the resulting count data. However, the Poisson regression requires assumptions of constant mean and variance equal to the (constant) mean in the experimental units. Such requirements may not be satisfied by the data of a clinical trial. An alternative method of analysis for such data is to use a permutation t-test. This is a distribution-free method. In this paper, results of a simulation study comparing the two methods--the Poisson regression and the permutation t-test--are presented. Effects of overdispersion and deviation of the assumptions of Poisson regression are also evaluated.

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