1 citations · 1 across the 4 of their papers we have counts for
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Spatially varying distributed lag non-linear models using Laplacian P-splines
Sara Rutten, Thomas Neyens, Elisa Duarte +2
Although distributed lag non-linear models (DLNMs) are commonly used to quantify delayed and non-linear exposure-response relationships, most existing applications assume that thes…
Distributed lag non-linear models with spatial effect modification using Laplacian P-splines
Sara Rutten, Thomas Neyens, Elisa Duarte +2
Distributed lag non-linear models (DLNMs) are a popular approach to flexibly model the effect of time-delayed exposures. Classical DLNMs specify a common exposure-lag-response rela…
A Bayesian Geoadditive Model for Spatial Disaggregation
Sara Rutten, Thomas Neyens, Elisa Duarte +1
We present a novel Bayesian spatial disaggregation model for count data, providing fast and flexible inference at high resolution. First, it incorporates non-linear covariate effec…
Distributed lag non-linear models with Laplacian-P-splines for analysis of spatially structured time series
Sara Rutten, Bryan Sumalinab, Oswaldo Gressani +4
Distributed lag non-linear models (DLNM) have gained popularity for modeling nonlinear lagged relationships between exposures and outcomes. When applied to spatially referenced dat…