title: Fitting E(max) models to clinical trial dose-response data.
abstract: We consider fitting Emax models to the primary endpoint for a parallel group dose–response clinical trial. Such models can be difficult to fit using Maximum Likelihood if the data give little information about the maximum possible response. Consequently, we consider alternative models that can be derived as limiting cases, which can usually be fitted. Furthermore we propose two model selection procedures for choosing between the different models. These model selection procedures are compared with two model selection procedures which have previously been used. In a simulation study we find that the model selection procedure that performs best depends on the underlying true situation. One of the new model selection procedures gives what may be regarded as the most robust of the procedures.
authors.affiliation: Simon Kirby, Statistics, Pfizer Limited, Sandwich, Kent, UK. simon.kirby@pfizer.com
authors.forename: Simon
authors.initials: S
authors.lastname: Kirby
authors.forename: Phil
authors.initials: P
authors.lastname: Brain
authors.forename: Byron
authors.initials: B
authors.lastname: Jones
mesh_terms: D002986:Clinical Trials as Topic; D003198:Computer Simulation; D004305:Dose-Response Relationship, Drug; D006801:Humans; D015233:Models, Statistical