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Bayesian Analysis of Realistically Complex Models

Author

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  • N. G. Best
  • D. J. Spiegelhalter
  • A. Thomas
  • C. E. G. Brayne

Abstract

Models with complex structure arise in many social science applications and appear natural candidates for the use of Markov chain Monte Carlo methods for inference. Conditional independence assumptions simplify the model specification and make estimation using Gibbs sampling particularly appropriate. Two examples are discussed: random effects models for repeated ordered categorical data and sensitivity analysis to assumptions concerning the mechanism underlying informative drop‐out in a longitudinal study. The use of a program bugs is demonstrated.

Suggested Citation

  • N. G. Best & D. J. Spiegelhalter & A. Thomas & C. E. G. Brayne, 1996. "Bayesian Analysis of Realistically Complex Models," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(2), pages 323-342, March.
    • Handle: RePEc:bla:jorssa:v:159:y:1996:i:2:p:323-342
    DOI: 10.2307/2983178
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    Cited by:

    1. Opher Baron & Iman Hajizadeh & Joseph Milner, 2011. "Now Playing: DVD Purchasing for a Multilocation Rental Firm," Manufacturing & Service Operations Management, INFORMS, vol. 13(2), pages 209-226, April.
    2. Zhiyong Zhang & Lijuan Wang, 2013. "Methods for Mediation Analysis with Missing Data," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 154-184, January.
    3. Puustelli, Anne & Koskinen, Lasse & Luoma, Arto, 2008. "Bayesian modelling of financial guarantee insurance," Insurance: Mathematics and Economics, Elsevier, vol. 43(2), pages 245-254, October.
    4. Neil Spencer, 2002. "Combining Modelling Strategies to Analyse Teaching Styles Data," Quality & Quantity: International Journal of Methodology, Springer, vol. 36(2), pages 113-127, May.
    5. Higgs, Megan Dailey & Hoeting, Jennifer A., 2010. "A clipped latent variable model for spatially correlated ordered categorical data," Computational Statistics & Data Analysis, Elsevier, vol. 54(8), pages 1999-2011, August.
    6. Paul C. Lambert & Lucinda J. Billingham & Nicola J. Cooper & Alex J. Sutton & Keith R. Abrams, 2008. "Estimating the cost‐effectiveness of an intervention in a clinical trial when partial cost information is available: a Bayesian approach," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 67-81, January.

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