Kianifard F, Gallo P P
Biostatistics Department, Hoechst-Roussel Pharmaceuticals, Somerville, New Jersey 08876-1258, USA.
J Biopharm Stat. 1995 Mar;5(1):115-29. doi: 10.1080/10543409508835101.
Generalized linear models (GLM) are now widely used in analyzing data from clinical trials and in epidemiological studies. In Poisson regression, which fits in the framework of a GLM, the response variable is a count that follows the Poisson distribution. This article describes the basic methodology of Poisson regression analysis and its application to clinical research. Overdispersion, model diagnostics, and sample size issues are discussed. The methodology is illustrated on a data set from a clinical trial for the treatment of bladder cancer, using a new procedure (PROC GENMOD) in the statistical package SAS.
广义线性模型（GLM）如今广泛应用于分析来自临床试验的数据以及流行病学研究。在符合GLM框架的泊松回归中，响应变量是服从泊松分布的计数。本文描述了泊松回归分析的基本方法及其在临床研究中的应用。讨论了过度离散、模型诊断和样本量问题。使用统计软件包SAS中的一个新过程（PROC GENMOD），在一个膀胱癌治疗临床试验的数据集上展示了该方法。
