title: Performance and sample size requirements of Bayesian methods for binary outcomes in fixed-dose combination drug studies.
abstract: We develop a Bayesian analysis for the study of fixed-dose combinations of two or more drugs. The approach described here does not require knowledge of the dose-response relationships of the components or large sample approximations. We provide a procedure to estimate sample size in this context. In addition, we explore the performance of the Bayesian procedure in situations where existing methods are known to perform poorly.
authors.affiliation: Department of Mathematics and Statistics, Sam Houston State University, Huntsville, Texas 77341-2206, USA. mholt@shsu.edu
authors.forename: Melinda M
authors.initials: MM
authors.lastname: Holt
authors.forename: James D
authors.initials: JD
authors.lastname: Stamey
authors.forename: John W
authors.initials: JW
authors.lastname: Seaman
authors.forename: Dean M
authors.initials: DM
authors.lastname: Young
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016010:Binomial Distribution; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D004357:Drug Synergism; D004359:Drug Therapy, Combination; D006801:Humans; D009010:Monte Carlo Method; D004364:Pharmaceutical Preparations / Q000008:administration & dosage; D018401:Sample Size
chemical_list: D004364:Pharmaceutical Preparations