title: Poisson regression analysis in clinical research.
abstract: 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.
authors.affiliation: Biostatistics Department, Hoechst-Roussel Pharmaceuticals, Somerville, New Jersey 08876-1258, USA.
authors.forename: F
authors.initials: F
authors.lastname: Kianifard
authors.forename: P P
authors.initials: PP
authors.lastname: Gallo
mesh_terms: D004827:Epilepsy / Q000453:epidemiology; D006801:Humans; D008432:Mathematical Computing; D008954:Models, Biological; D010919:Placebos; D016012:Poisson Distribution; D011736:Pyridoxine / Q000627:therapeutic use; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D012044:Regression Analysis; D013852:Thiotepa / Q000627:therapeutic use; D001749:Urinary Bladder Neoplasms / Q000188:drug therapy
chemical_list: D010919:Placebos; D013852:Thiotepa; D011736:Pyridoxine