Bayesian hierarchical models for food frequency assessment

DOI10.1002/CJS.10052zbMath1327.62509OpenAlexW2084001080MaRDI QIDQ3589857

Andrew B. Lawson, Daniela K. Nitcheva, Hae-Ryoung Song

Publication date: 20 September 2010

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

Full work available at URL: https://doi.org/10.1002/cjs.10052

zbMATH Keywords

gammaclassicalmeasurement error modelsskew-Gaussianfood frequency questionnaireBerksondoubly labelled waterlog-Gaussian

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to social sciences (62P25)

Cites Work

• Structured Measurement Error in Nutritional Epidemiology
• A new class of measurement-error models, with applications to dietary data
• Bayesian Smoothing and Regression Splines for Measurement Error Problems
• Identifiability, Improper Priors, and Gibbs Sampling for Generalized Linear Models
• Bayesian Measures of Model Complexity and Fit
• Logistic Regression with Exposure Biomarkers and Flexible Measurement Error
• Prior distributions for variance parameters in hierarchical models (Comment on article by Browne and Draper)
• Deviance information criteria for missing data models

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