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Hierarchical Bayesian Modeling of Spatially Correlated Health Service Outcome and Utilization Rates

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  • Ying C. MacNab

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  • Ying C. MacNab, 2003. "Hierarchical Bayesian Modeling of Spatially Correlated Health Service Outcome and Utilization Rates," Biometrics, The International Biometric Society, vol. 59(2), pages 305-315, June.
  • Handle: RePEc:bla:biomet:v:59:y:2003:i:2:p:305-315
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    File URL: http://hdl.handle.net/10.1111/1541-0420.00037
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    References listed on IDEAS

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    1. Ying C. MacNab & C. B. Dean, 2001. "Autoregressive Spatial Smoothing and Temporal Spline Smoothing for Mapping Rates," Biometrics, The International Biometric Society, vol. 57(3), pages 949-956, September.
    2. Julian Besag & Jeremy York & Annie Mollié, 1991. "Bayesian image restoration, with two applications in spatial statistics," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(1), pages 1-20, March.
    3. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
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    Cited by:

    1. Ying C. MacNab & Patrick J. Farrell & Paul Gustafson & Sijin Wen, 2004. "Estimation in Bayesian Disease Mapping," Biometrics, The International Biometric Society, vol. 60(4), pages 865-873, December.
    2. Geòrgia Escaramís & Josep L. Carrasco & Carlos Ascaso, 2008. "Detection of Significant Disease Risks Using a Spatial Conditional Autoregressive Model," Biometrics, The International Biometric Society, vol. 64(4), pages 1043-1053, December.
    3. Lee, Dae-Jin & Durbán, María, 2009. "Smooth-CAR mixed models for spatial count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2968-2979, June.
    4. Ignacio Abásolo & Miguel Negrín-Hernández & Jaime Pinilla, 2014. "Equity in specialist waiting times by socioeconomic groups: evidence from Spain," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 15(3), pages 323-334, April.
    5. MacNab, Ying C. & Lin, Yi, 2009. "On empirical Bayes penalized quasi-likelihood inference in GLMMs and in Bayesian disease mapping and ecological modeling," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2950-2967, June.
    6. Ugarte, M.D. & Goicoa, T. & Militino, A.F., 2009. "Empirical Bayes and Fully Bayes procedures to detect high-risk areas in disease mapping," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2938-2949, June.

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