6 papers
Laplacian-P-splines for shared Gamma frailty models applied to clustered right-censored time-to-event data
Piotr Lewczuk, Oswaldo Gressani, Steven Abrams +1
Shared frailty models have been proposed to accommodate unmeasured cluster-specific risk factors through the inclusion of a common latent frailty term. Among possible frailty distr…
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 Time-Series Model for Areal Data Using Area-Specific Gaussian Processes with Spatially Correlated Hyperparameters
Alejandro Rozo Posada, Oswaldo Gressani, Christel Faes +4
In many applied settings, areal data are observed repeatedly over long time periods, as commonly occurs in infectious disease surveillance and environmental or demographic monitori…
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…