Efficient estimation of Cox model with random change point.
Stat Med
; 43(6): 1213-1226, 2024 Mar 15.
Article
en En
| MEDLINE
| ID: mdl-38247108
ABSTRACT
In clinical studies, the risk of a disease may dramatically change when some biological indexes of the human body exceed some thresholds. Furthermore, the differences in individual characteristics of patients such as physical and psychological experience may lead to subject-specific thresholds or change points. Although a large literature has been established for regression analysis of failure time data with change points, most of the existing methods assume the same, fixed change point for all study subjects. In this paper, we consider the situation where there exists a subject-specific change point and two Cox type models are presented. The proposed models also offer a framework for subgroup analysis. For inference, a sieve maximum likelihood estimation procedure is proposed and the asymptotic properties of the resulting estimators are established. An extensive simulation study is conducted to assess the empirical performance of the proposed method and indicates that it works well in practical situations. Finally the proposed approach is applied to a set of breast cancer data.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Modelos de Riesgos Proporcionales
Tipo de estudio:
Clinical_trials
/
Prognostic_studies
Límite:
Humans
Idioma:
En
Revista:
Stat Med
Año:
2024
Tipo del documento:
Article
País de afiliación:
China