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.

Key Words:

• Bayesian methods
• Meta-analysis
• Penalized likelihood
• Proportional hazards model
• Time-to-event

Notes

Note. In parentheses are the average of the model-based standard errors of log HR from each of the simulation runs for frequentists methods and the average of the posterior standard deviations of log HR from each of the runs for the Bayesian methods.

Note. IP represents the Bayesian approach with informative priors.

Note. IP represents the Bayesian approach with informative priors.

Note. In parentheses are the average of the model-based standard errors of log HR from each of the simulation runs for frequentists methods and the average of the posterior standard deviations of log HR from each of the runs for the Bayesian methods.