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Thursday, May 30
Data Science Techologies
Practice and Applications
Data Science Applications E-Posters, I
Thu, May 30, 3:00 PM - 4:00 PM
Grand Ballroom Foyer

Hypothesis Testing in Nonlinear Function on Scalar Regression with Application to Child Growth Study (306276)

*Mityl Biswas, NC State University 

Keywords: Hypothesis testing, kernel machine, nonlinear function on scalar regression

We propose a kernel machine based hypothesis testing procedure in nonlinear function-on-scalar regression model. Our research is motivated by the Newborn Epigenetic Study (NEST) where the question of interest is whether a pre-specified group of toxic metals is associated with child growth. We take the child growth trajectory as the functional response, and model the toxic metal measurements jointly using a nonlinear function. We use a kernel machine approach to model the unknown function and transform the hypothesis of no effect to an appropriate variance components test. We demonstrate our proposed methodology using a simulation study and by applying it to analyze the NEST data.