ESTIMATION AND INFERENCE FOR EXPOSURE EFFECTS WITH LATENCY IN THE COX PROPORTIONAL HAZARDS MODEL IN THE PRESENCE OF EXPOSURE MEASUREMENT ERROR

• 成果类型: Article
• 署名作者: Peskoe, Sarah B.; Zhang, Ning; Spiegelman, Donna; Wang, Molin
• 署名单位: Duke University; Harvard University; Harvard T.H. Chan School of Public Health; Yale University
• 刊物名称: ANNALS OF APPLIED STATISTICS
• ISSN/ISSBN: 1932-6157
• DOI: 10.1214/22-AOAS1682
• 发表日期: 2023
• 页码: 1574-1591
• 关键词: particulate air-pollution; coronary-heart-disease; confidence-intervals; ambient concentrations; matter panel; lung-cancer; regression; RISK; association; mortality

摘要

Researchers are often interested in estimating the effects of time-varying exposures on health outcomes. The latency period, defined as the critical pe-riod of susceptibility, can be an important component of exposure effect as-sessment. Although it is widely known that many environmental, nutritional, and other exposure measurements are prone to error and are also likely to act only during a critical time window of susceptibility, no one has yet considered the impact of this on the estimation of latency parameters in survival mod-els. In this paper we derived methods for point and interval estimation for the latency parameter and the regression coefficients in rare disease situations. Under a linear measurement model, although the estimated hazard ratios are biased, as has been previously demonstrated, we show that the latency pa-rameter is approximately unbiased. Simulations and an illustrative example investigating the prospective association between PM2.5 and lung cancer in-cidence in the Nurses' Health Study are included to evaluate the performance of our method.