Estimation of direct effects for survival data by using the Aalen additive hazards model

• 成果类型: Article
• 署名作者: Martinussen, Torben; Vansteelandt, Stijn; Gerster, Mette; Hjelmborg, Jacob von Bornemann
• 署名单位: University of Copenhagen; Ghent University; University of London; London School of Hygiene & Tropical Medicine; University of Southern Denmark
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/j.1467-9868.2011.00782.x
• 发表日期: 2011
• 页码: 773-788
• 关键词: MARGINAL STRUCTURAL MODELS; regression; interventions; Mediation

摘要

We extend the definition of the controlled direct effect of a point exposure on a survival outcome, other than through some given, time-fixed intermediate variable, to the additive hazard scale. We propose two-stage estimators for this effect when the exposure is dichotomous and randomly assigned and when the association between the intermediate variable and the survival outcome is confounded only by measured factors, which may themselves be affected by the exposure. The first stage of the estimation procedure involves assessing the effect of the intermediate variable on the survival outcome via Aalen's additive regression for the event time, given exposure, intermediate variable and confounders. The second stage involves applying Aalen's additive model, given the exposure alone, to a modified stochastic process (i.e. a modification of the observed counting process based on the first-stage estimates). We give the large sample properties of the estimator proposed and investigate its small sample properties by Monte Carlo simulation. A real data example is provided for illustration.