A semiparametric risk score for physical activity
| Autor: | Raymond J. Carroll, David Ruppert, E. Christi Thompson, Erjia Cui |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Statistics and Probability
Models Statistical National Health and Nutrition Examination Survey Epidemiology Computer science Statistics & Probability Generalized additive model Bayes Theorem Nutrition Surveys Bayesian inference Article Term (time) Nonlinear system Risk Factors Component (UML) Statistics Linear Models Humans 0104 Statistics 1117 Public Health and Health Services Computational problem Additive model Exercise |
| Zdroj: | Stat Med |
| ISSN: | 1097-0258 0277-6715 |
| DOI: | 10.1002/sim.9262 |
| Popis: | We develop a generalized partially additive model to build a single semiparametric risk scoring system for physical activity across multiple populations. A score comprised of distinct and objective physical activity measures is a new concept that offers challenges due to the nonlinear relationship between physical behaviors and various health outcomes. We overcome these challenges by modelling each score component as a smooth term, an extension of generalized partially linear single-index models. We use penalized splines and propose two inferential methods, one using profile likelihood and a nonparametric bootstrap, the other using a full Bayesian model, to solve additional computational problems. Both methods exhibit similar and accurate performance in simulations. These models are applied to the National Health and Nutrition Examination Survey (NHANES) and quantify nonlinear and interpretable shapes of score components for all-cause mortality. |
| Databáze: | OpenAIRE |
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