Cause-specific hazard Cox models with partly interval censoring - Penalized likelihood estimation using Gaussian quadrature.
Stat Methods Med Res
; : 9622802241262526, 2024 Jul 25.
Article
in En
| MEDLINE
| ID: mdl-39053566
ABSTRACT
The cause-specific hazard Cox model is widely used in analyzing competing risks survival data, and the partial likelihood method is a standard approach when survival times contain only right censoring. In practice, however, interval-censored survival times often arise, and this means the partial likelihood method is not directly applicable. Two common remedies in practice are (i) to replace each censoring interval with a single value, such as the middle point; or (ii) to redefine the event of interest, such as the time to diagnosis instead of the time to recurrence of a disease. However, the mid-point approach can cause biased parameter estimates. In this article, we develop a penalized likelihood approach to fit semi-parametric cause-specific hazard Cox models, and this method is general enough to allow left, right, and interval censoring times. Penalty functions are used to regularize the baseline hazard estimates and also to make these estimates less affected by the number and location of knots used for the estimates. We will provide asymptotic properties for the estimated parameters. A simulation study is designed to compare our method with the mid-point partial likelihood approach. We apply our method to the Aspirin in Reducing Events in the Elderly (ASPREE) study, illustrating an application of our proposed method.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Stat Methods Med Res
/
Stat. methods med. res
/
Statistical methods in medical research
Year:
2024
Document type:
Article
Affiliation country:
Australia
Country of publication:
United kingdom