1. Analysis of clustered competing risks data using subdistribution hazard models with multivariate frailties.
- Author
-
Ha, Il Do, Christian, Nicholas J., Jeong, Jong-Hyeon, Park, Junwoo, and Lee, Youngjo
- Subjects
- *
CLINICAL trials , *REGRESSION analysis , *FRAGILITY (Psychology) , *HETEROGENEITY , *STATISTICAL reliability , *BREAST cancer , *TAMOXIFEN , *BREAST tumors , *COMPUTER simulation , *MEDICAL cooperation , *MULTIVARIATE analysis , *PROBABILITY theory , *RESEARCH , *RESEARCH funding , *RELATIVE medical risk , *PROPORTIONAL hazards models - Abstract
Competing risks data often exist within a center in multi-center randomized clinical trials where the treatment effects or baseline risks may vary among centers. In this paper, we propose a subdistribution hazard regression model with multivariate frailty to investigate heterogeneity in treatment effects among centers from multi-center clinical trials. For inference, we develop a hierarchical likelihood (or h-likelihood) method, which obviates the need for an intractable integration over the frailty terms. We show that the profile likelihood function derived from the h-likelihood is identical to the partial likelihood, and hence it can be extended to the weighted partial likelihood for the subdistribution hazard frailty models. The proposed method is illustrated with a dataset from a multi-center clinical trial on breast cancer as well as with a simulation study. We also demonstrate how to present heterogeneity in treatment effects among centers by using a confidence interval for the frailty for each individual center and how to perform a statistical test for such heterogeneity using a restricted h-likelihood. [ABSTRACT FROM AUTHOR]
- Published
- 2016
- Full Text
- View/download PDF