Bayesian latent variable modelling of multivariate spatio-temporal variation in cancer mortality

DOI10.1177/0962280207081243zbMath1161.62075OpenAlexW2118900185WikidataQ51905987 ScholiaQ51905987MaRDI QIDQ3628762

Evangelia Tzala, Nicky G. Best

Publication date: 24 May 2009

Published in: Statistical Methods in Medical Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/0962280207081243

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (11)

Bayesian shared spatial-component models to combine and borrow strength across sparse disease surveillance sources ⋮ Multichart schemes for detecting changes in disease incidence ⋮ Bayesian joint modeling of correlated counts data with application to adverse birth outcomes ⋮ Bayesian 2-stage space-time mixture modeling with spatial misalignment of the exposure in small area health data ⋮ Zero-Inflated Spatial Models: Application and Interpretation ⋮ Bayesian Non-Parametric Factor Analysis for Longitudinal Spatial Surfaces ⋮ Spatial interpolation of high-frequency monitoring data ⋮ A Bayesian factor model for spatial panel data with a separable covariance approach ⋮ Dynamic Multiscale Spatiotemporal Models for Gaussian Areal Data ⋮ Bayesian factor analysis for spatially correlated data: application to cancer incidence data in Scotland ⋮ Multivariate spatio-temporal models for high-dimensional areal data with application to longitudinal employer-household dynamics

Uses Software

• MLwiN

Cites Work

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• Bayesian modelling of spatial heterogeneity in disease maps with application to German cancer mortality data
• A general model for the analysis of multilevel data
• Latent Variable Analysis of Multivariate Spatial Data
• A comparison of Bayesian spatial models for disease mapping
• Towards joint disease mapping
• Issues in the mapping of two diseases
• A Shared Component Model for Detecting Joint and Selective Clustering of Two Diseases
• Generalized common spatial factor model
• Bayesian Factor Analysis for Spatially Correlated Data, With Application to Summarizing Area-Level Material Deprivation From Census Data
• Parameterization and Bayesian Modeling
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)

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