A double exponential gamma-frailty model for clustered survival data

Abstract

We propose a double exponential gamma-frailty model for clustered survival data. This model addresses the limitation of shared gamma-frailty models, where the marginal effects of covariates diminish over time. To estimate parameters, we utilise a sieve maximum likelihood approach and employ Bernstein polynomials for approximating nondecreasing cumulative baseline functions. The estimators' asymptotic properties are also provided. The proposed method is demonstrated through numerical simulations and survival data from a diabetic retinopathy study and a colorectal cancer study.

Keywords:

• clustered data
• frailty
• survival analysis
• Bernstein polynomial
• sieve estimator

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 12171329], the Academy for Multidisciplinary Studies of Capital Normal University, and the National Institute for Health Care Management Foundation (NIH) [grant number UL1 TR002345].