Interval estimation of random effects in proportional hazards models with frailties

2013/01/29 by Il Do Ha, Florin Vaida, Youngjo Lee
Mathematics · Social Sciences · #Insurance, Mortality, Demography, Risk Management #Statistical Methods and Bayesian Inference #Statistical Methods and Inference

paper · doi:10.1177/0962280212474059

openalex publication_date 2013/01/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/24

Abstract

Semi-parametric frailty models are widely used to analyze clustered survival data. In this article, we propose the use of the hierarchical likelihood interval for individual frailties. We study the relationship between hierarchical likelihood, empirical Bayesian, and fully Bayesian intervals for frailties. We show that our proposed interval can be interpreted as a frequentist confidence interval and Bayesian credible interval under a uniform prior. We also propose an adjustment of the proposed interval to avoid null intervals. Simulation studies show that the proposed interval preserves the nominal confidence level. The procedure is illustrated using data from a multicenter lung cancer clinical trial.

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