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A Semiparametric Single-Index Risk Score Across Populations.


ABSTRACT: 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-index model 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.

SUBMITTER: Ma S 

PROVIDER: S-EPMC5839692 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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A Semiparametric Single-Index Risk Score Across Populations.

Ma Shujie S   Ma Yanyuan Y   Wang Yanqing Y   Kravitz Eli S ES   Carroll Raymond J RJ  

Journal of the American Statistical Association 20170718 520


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-index model is fit. The partially linear aspect of the problem is allowed to differ in each population and disease. However, and crucially, the single-index it  ...[more]

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2024-06-30 | GSE232027 | GEO