Bayesian hierarchical models for disease mapping applied to contagious pathologies

mapping spatial variation of disease using classic and bayesian models

abstract   disease mapping includes a set of statistical techniques that lead to provide clean maps based on estimation of the incidence, prevalence and mortality rates for the users to be able to estimate the distribution of disease reliably. the main aims of disease mapping are to: describe the spatial variation in disease incidence for the formulation of etiological hypotheses; identify area...

A hierarchical Bayesian approach to multiple testing in disease mapping

We propose a Bayesian approach to multiple testing in disease mapping. This study was motivated by a real example regarding the mortality rate for lung cancer, males, in the Tuscan region (Italy). The data are relative to the period 1995-1999 for 287 municipalities. We develop a tri-level hierarchical Bayesian model to estimate for each area the posterior classification probability that is the ...

Analysis of Hierarchical Bayesian Models for Large Space Time Data of the Housing Prices in Tehran

Housing price data is correlated to their location in different neighborhoods and their correlation is type of spatial (location). The price of housing is varius in different months, so they also have a time correlation. Spatio-temporal models are used to analyze this type of the data. An important purpose of reviewing this type of the data is to fit a suitable model for the spatial-temporal an...

Comparing MCMC and INLA for disease mapping with Bayesian hierarchical models

Introduction Bayesian hierarchical models with random effects are one of the most widely used methods in modern disease mapping, as a superior alternative to standardized ratios. These models are traditionally fitted through Markov Chain Monte Carlo sampling (MCMC). Due to the nature of the hierarchical models and random effects, the convergence of MCMC is very slow and unpredictable. Recently,...

Bayesian Hierarchical Models 1 Running head: BAYESIAN HIERARCHICAL MODELS Bayesian Hierarchical Models