Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Bayesian Analysis for Random Effects Binomial Regression

  • Kim, Dal-Ho (Department of Statistics, Kyungpook National University) ;
  • Kim, Eun-Young (Department of Statistics, Kyungpook National University)
  • Published : 2000.12.01
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Abstract

In this paper, we investigate the Bayesian approach to random effect binomial regression models with improper prior due to the absence of information on parameter. We also propose a method of estimating the posterior moments and prediction and discuss some general methods for studying model assessment. The methodology is illustrated with Crowder's Seeds Data. Markov Chain Monte Carlo techniques are used to overcome the computational difficulties.

Keywords

References

  1. The American Statistician v.51 Bayesian Binomial Regression : Redicting Survival at a Trauma Center Bedrick, E.J.;Christensen, R.;Johnson, W.
  2. Journal of American Statistical Association v.88 Approximate Inference in Generalized Linear Mixed Models Breslow, N.E.;Clayton, D.G.
  3. The American Statistician v.49 Understanding the Metropolis-Hastings Algorithm Chib, S.;Greenberg, E.
  4. Applied Statistics v.27 Beta-binomial Anova for Proportions Crowder, M.J.
  5. Biometrics v.85 Model Choice : a posterior predictive loss approach Gelfand, A.E.;Ghosh, S.K.
  6. Communication in Statistics, Theory and Methods v.20 Gibbs Sampling for Marginal Posterior Expectations Gelfand, A.E.;Smith, A.F.M.
  7. Statistica Sinica v.6 Posterior Predictive assessment of model fitness via realized discrepancies(with discussions) Gelman, A.;Meng, X.L.;Stern, H.
  8. Statistics Science v.7 Inference from Iterative Simulation (with discussion) Gelman, A.;Rubin, D.B.
  9. Journal of American Statistical Association v.93 Generalized Linear Models for Small-Area Estimation Ghosh, M.;Natarajan, K.;Stroud, T.W.F.;Carlin, B.P.
  10. Applied Statistics v.41 Adaptive Rejection Sampling for Gibbs Sampling Gilks, W.R.;Wild, P.
  11. Journal of American Statistical Association v.86 On Bayesian Analysis of Generalized Linear Models Using Jeffreys' Prior Ibrahim, J.G.;Laud, P.W.
  12. Journal of the Royal Statistical Society, Ser. B v.57 Predictive model selection Laud, P.;Ibrahim, J.
  13. Biometrika v.59 Bayesian Methods for Binomial Data Leonard, T.
  14. Journal of the Royal Statistical Society, Ser. B v.34 Bayes Estimates for the Linear Model (with discussion) Lindley, D.V.;Smith, A.F.M.
  15. Biometrika v.82 A Note on the Existence of the Posterior Distribution for a Class of Mixed Models for Binomial Responses Natarajan, R.;McCulloch, C.E.
  16. Journal of the Royal Statistical Society, Ser. B v.24 Discussion on the Paper by Professor Lindley and Dr Smith Nelder, J.A.
  17. Journal of the Royal Statistical Society, Ser. A v.135 Generalized Linear Models Nelder, J.A.;Wedderburn, R.W.M.
  18. Journal of American Statistical Association v.86 Generalized Linear Models with Random Effects : A Gibbs Sampling Approach Zeger, S.L.;Karim, M.R.
  19. Journal of Econometrics v.25 Bayesian Analysis of Dichotomous Quantal Response Models Zellner, A.;Rossi, P.E.
  20. Model Checking and Model Improvement Gelman, A.;Meng X.L.;W.R. Gilks(et al.)(ed.)