A Semiparametric Single-Index Risk Score Across Populations

• 成果类型: Article
• 署名作者: Ma, Shujie; Ma, Yanyuan; Wang, Yanqing; Kravitz, Eli S.; Carroll, Raymond J.
• 署名单位: University of California System; University of California Riverside; University of South Carolina System; University of South Carolina Columbia; Fred Hutchinson Cancer Center; Texas A&M University System; Texas A&M University College Station; University of Technology Sydney
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2016.1222944
• 发表日期: 2017
• 页码: 1648-1662
• 关键词: healthy eating index-2005; partial linear-models; polynomial spline; mediterranean diet; variable selection; local asymptotics; Chronic Disease; regression; cancer; patterns

摘要

We consider a problem motivated by issues in nutritional epidemiology, across diseases and populations. In this area, it is becoming increasingly common for diseases to be modeled by a single diet score, such as the Healthy Eating Index, the Mediterranean Diet Score, etc. For each disease and for each population, a partially linear single-indexmodel is fit. The partially linear aspect of the problem is allowed to differ in each population and disease. However, and crucially, the single-index itself, having to do with the diet score, is common to all diseases and populations, and the nonparametrically estimated functions of the single-index are the same up to a scale parameter. Using B-splines with an increasing number of knots, we develop a method to solve the problem, and display its asymptotic theory. An application to the NIH-AARP Study of Diet and Health is described, where we show the advantages of using multiple diseases and populations simultaneously rather than one at a time in understanding the effect of increased Milk consumption. Simulations illustrate the properties of the methods. Supplementary materials for this article are available online.