1. Smoothing spline choice in distributed lag nonlinear models for statistical modeling of count data.
- Author
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Nguyen, Mien T. N., Nguyen, Vu A., and Nguyen, Man V. M.
- Subjects
SMOOTHNESS of functions ,ENVIRONMENTAL exposure ,STATISTICAL models ,ENVIRONMENTAL health ,SPLINES - Abstract
The distributed lag nonlinear model (DLNM) effectively describes the nonlinear and delayed effects in time-series investigations about some environmental exposures and health outcomes. In DLNM, nonparametric smooth functions are employed to fit the delayed nonlinear relationships between the continuous predictors and the count-dependent variable. This study focused on the cubic B-splines and cubic polynomials as reparameterization tools for these smooth functions. Furthermore, for each scenario, we apply two frameworks of the DLNM, including the classical DLNM and the penalized DLNM. A simulation study is undertaken to evaluate how well these proposed models perform, using criteria such as mean squared errors, mean absolute errors, and AIC. The penalized DLNM with a B-spline basis achieves the best performance in predicting the outcome. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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