title: Comparison of Bayesian and frequentist meta-analytical approaches for analyzing time to event data.
abstract: Using meta-analysis in health care research is a common practice. Here we are interested in methods used for analysis of time-to-event data. Particularly, we are interested in their performance when there is a low event rate. We consider three methods based on the Cox proportional hazards model, including a Bayesian approach. A formal comparison of the methods is conducted using a simulation study. In our simulation we model two treatments and consider several scenarios.
authors: Institute for Health Care Research and Improvement, Baylor Health Care System, Dallas, Texas 75201, USA. Monica.Bennett@BaylorHealth.edu
authors: Monica M
authors: MM
authors: Bennett
authors: Brenda J
authors: BJ
authors: Crowe
authors: Karen L
authors: KL
authors: Price
authors: James D
authors: JD
authors: Stamey
authors: John W
authors: JW
authors: Seaman
mesh_terms: D001499:Bayes Theorem; D002986:Clinical Trials as Topic / Q000379:methods; D003198:Computer Simulation / Q000639:trends; D006801:Humans; D015201:Meta-Analysis as Topic; D016016:Proportional Hazards Models; D012107:Research Design; D013223:Statistics as Topic / Q000379:methods*; D013997:Time Factors