Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data

• 成果类型: Article
• 署名作者: Rizopoulos, Dimitris; Verbeke, Geert; Lesaffre, Emmanuel
• 署名单位: Erasmus University Rotterdam; Erasmus MC; KU Leuven; Hasselt University
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/j.1467-9868.2008.00704.x
• 发表日期: 2009
• 页码: 637-654
• 关键词: em algorithm; proportional-hazards; likelihood approach

摘要

A common objective in longitudinal studies is the joint modelling of a longitudinal response with a time-to-event outcome. Random effects are typically used in the joint modelling framework to explain the interrelationships between these two processes. However, estimation in the presence of random effects involves intractable integrals requiring numerical integration. We propose a new computational approach for fitting such models that is based on the Laplace method for integrals that makes the consideration of high dimensional random-effects structures feasible. Contrary to the standard Laplace approximation, our method requires much fewer repeated measurements per individual to produce reliable results.