Nonsmooth backfitting for the excess risk additive regression model with two survival time scales

• 成果类型: Article
• 署名作者: Hiabu, M.; Nielsen, J. P.; Scheike, T. H.
• 署名单位: University of Sydney; City St Georges, University of London; University of Copenhagen
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asaa058
• 发表日期: 2021
• 页码: 491506
• 关键词: estimator

摘要

We consider an extension of Aalen's additive regression model that allows covariates to have effects that vary on two different time scales. The two time scales considered are equal up to a constant for each individual and vary across individuals, such as follow-up time and age in medical studies or calendar time and age in longitudinal studies. The model was introduced in Scheike (2001), where it was solved using smoothing techniques. We present a new backfitting algorithm for estimating the structured model without having to use smoothing. Estimators of the cumulative regression functions on the two time scales are suggested by solving local estimating equations jointly on the two time scales. We provide large-sample properties and simultaneous confidence bands. The model is applied to data on myocardial infarction, providing a separation of the two effects stemming from time since diagnosis and age.