Ensemble post-processing is a promising method to obtain flexible distributed lag models: : A simulation study of time series of air pollution and daily mortality.

Last updated on 22-8-2019 by Anonymous (niet gecontroleerd)

Public Access


Peer reviewed scientific article


Distributed lag models (DLM) are regression models that include multiple lagged exposure variables as covariates. They are frequently used to model the relationship between daily mortality and short-term air pollution exposures. Specifying a maximum lag number is but one of the difficulties in using a DLM for environmental epidemiology. We propose an easily extendible ensemble post-processing approach. The resultant estimates are both more parsimonious, approaching zero with increasing lag, and more efficient. The benefits are shown to be robust under various simulation scenario’s and illus…

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