Bayesian Spatiotemporal Modelling
Cross-source consensus on Bayesian Spatiotemporal Modelling from 1 sources and 7 claims.
1 sources · 7 claims
Uses
How it works
Evidence quality
Highlighted claims
- The study used a hierarchical Bayesian framework estimated via Integrated Nested Laplace Approximation in R 4.5.0. — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
- Spatial structure was modelled using Besag-York-Mollie priors, and temporal dependence used a first-order random walk. — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
- Four nested models were tested, progressively adding environmental, healthcare and demographic variable domains, with model selection based on DIC and WAIC. — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
- Neonatal mortality had the best predictive accuracy (R²=0.99), while under-5 mortality had the weakest fit (R²=0.60). — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
- Penalised complexity priors shrank spatial and temporal random effects toward zero unless the data supported heterogeneity. — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
- Island countries were linked to their nearest land neighbour so every country had at least one spatial neighbour and the model could be estimated without singularities. — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study
- The white-box Bayesian design allows policymakers to trace how covariates, spatial patterns and temporal trends contribute to risk estimates, supporting evidence-based planning. — Bayesian spatiotemporal modelling of neonatal, infant and under-5 mortality (2000–2022) in 41 Asian countries: a population-level observational study