Spatial modeling using frequentist approach for disease mapping

DOI10.1080/02664763.2012.711814OpenAlexW1984579286MaRDI QIDQ5127108

Mahmoud Torabi

Publication date: 21 October 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2012.711814

zbMATH Keywords

predictionBayesian computationdisease mappinggeneralized linear mixed modelconditional autoregressivegeographic epidemiology

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (3)

Spatio–temporal modeling for disease mapping using CAR and B‐spline smoothing ⋮ Spatiotemporal modeling of odds of disease ⋮ Hierarchical Bayesian bivariate disease mapping: analysis of children and adults asthma visits to hospital

Uses Software

• R
• WinBUGS
• dclone

Cites Work

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• Longitudinal data analysis using generalized linear models
• Hierarchical Bayes estimation of spatial statistics for rates
• A standard error for the estimated state vector of a state-space model
• Bayesian image restoration, with two applications in spatial statistics (with discussion)
• Spatio-temporal modelling of disease mapping of rates
• Estimating Equations for Parameters in Means and Covariances of Multivariate Discrete and Continuous Responses
• Hierarchical Spatio-Temporal Mapping of Disease Rates
• Approximate Inference in Generalized Linear Mixed Models
• Spatio-temporal modelling using B-spline for disease mapping: analysis of childhood cancer trends
• Estimability and Likelihood Inference for Generalized Linear Mixed Models Using Data Cloning

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