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Nonparametric Priors for Ordinal Bayesian Social Science Models: Specification and Estimation

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  • Gill, Jeff
  • Casella, George

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  • Gill, Jeff & Casella, George, 2009. "Nonparametric Priors for Ordinal Bayesian Social Science Models: Specification and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 453-454.
    • Handle: RePEc:bes:jnlasa:v:104:i:486:y:2009:p:453-454
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    Cited by:

    1. Takahiro Hoshino, 2013. "Semiparametric Bayesian Estimation for Marginal Parametric Potential Outcome Modeling: Application to Causal Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 108(504), pages 1189-1204, December.
    2. Minjung Kyung & Jeff Gill & George Casella, 2011. "Sampling schemes for generalized linear Dirichlet process random effects models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(3), pages 259-290, August.
    3. Kyung, Minjung & Gill, Jeff & Casella, George, 2009. "Characterizing the variance improvement in linear Dirichlet random effects models," Statistics & Probability Letters, Elsevier, vol. 79(22), pages 2343-2350, November.
    4. Brown, Sarah & Ghosh, Pulak & Pareek, Bhuvanesh & Taylor, Karl, 2021. "The protective role of saving: Bayesian analysis of British panel data," Journal of Empirical Finance, Elsevier, vol. 63(C), pages 57-72.
    5. J. R. Lockwood & Katherine E. Castellano & Benjamin R. Shear, 2018. "Flexible Bayesian Models for Inferences From Coarsened, Group-Level Achievement Data," Journal of Educational and Behavioral Statistics, , vol. 43(6), pages 663-692, December.

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