title: Between-within effects in survival models with cross-classified clustering: Application to the evaluation of the effectiveness of medical devices.
abstract: In many medical applications involving observational survival data there will be a cross-classification of doctors and hospitals, as well as an interest in controlling for potentially confounding doctor and hospital effects when evaluating the effectiveness of a medical intervention. In this paper, we propose the use of a between-within model with cross-classified random effects and show through simulation that it performs better than alternative models. A real data example illustrates the application of the proposed model in a study of the survival of hip implants. The proposed model has broad utility in determining the effectiveness of medical interventions.
authors.affiliation: 1 Kaiser Permanente, San Diego, USA.
authors.forename: Guy
authors.initials: G
authors.lastname: Cafri
authors.affiliation: 2 San Diego State University, San Diego, USA.
authors.forename: Juanjuan
authors.initials: J
authors.lastname: Fan
mesh_terms: D016000:Cluster Analysis; D004864:Equipment and Supplies / Q000592:standards*; D016013:Likelihood Functions; D016014:Linear Models; D019370:Observation; D016019:Survival Analysis
keywords: Random effects; between-within effects; cross-classified; frailty; survival