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Title: Bayesian Posterior Predictive Checks for Complex Models
Resulting in 1 citation.
1. Lynch, Scott M.
Western, Bruce
Bayesian Posterior Predictive Checks for Complex Models
Sociological Methods and Research 32,3 (February 2004): 301-335.
Also: http://smr.sagepub.com/content/32/3/301.abstract
Cohort(s): NLSY79
Publisher: Sage Publications
Keyword(s): Bayesian; Modeling, Fixed Effects; Modeling, Mixed Effects; Modeling, Multilevel; Modeling, Probit; Modeling, Random Effects

Permission to reprint the abstract has not been received from the publisher.

In sociological research, it is often difficult to compare nonnested models and to evaluate the fit of models in which outcome variables are not normally distributed. In this article, the authors demonstrate the utility of Bayesian posterior predictive distributions specif-ically, as well as a Bayesian approach to modeling more generally, in tackling these issues. First, they review the Bayesian approach to statistics and computation. Second, they discuss the evaluation of model fit in a bivariate probit model. Third, they discuss comparing fixed- and random-effects hierarchical linear models. Both examples high-light the use of Bayesian posterior predictive distributions beyond these particular cases. Copyright: 2004 Sage Publications
Bibliography Citation
Lynch, Scott M. and Bruce Western. "Bayesian Posterior Predictive Checks for Complex Models." Sociological Methods and Research 32,3 (February 2004): 301-335.