A unified framework for multiple-exposure DLNMs is developed with estimation, AIC selection, and stacking, applied to Ontario air pollution and respiratory mortality data where stacking detects significant mixture effects.
We included the seasonal trendh(t) = 0.5 sin(t/150)
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A Unified Framework for Multiple Exposure Distributed Lag Non-Linear Models for Air Pollution Epidemiology
A unified framework for multiple-exposure DLNMs is developed with estimation, AIC selection, and stacking, applied to Ontario air pollution and respiratory mortality data where stacking detects significant mixture effects.