A0410
Title: Statistical analysis of physical activity from NHANES
Authors: Andrada Ivanescu - Montclair State University (United States) [presenting]
Ciprian Crainiceanu - Johns Hopkins Bloomberg School of Public Health (United States)
Abstract: Functional regression models with functional predictors involve functional parameters for estimating the statistical associations. Basis expansions are employed to achieve nonparametric function estimation by establishing a mixed model representation with smooth functional model estimates. The framework offers a pathway for statistical methodology facilitated by the ability to employ functional regression with high-dimensional predictors. Implementations to the study of physical activity from NHANES illustrate the applicability of the proposed methods.
