Bayesian posterior predictive checks for complex methods  

Oleh:

Western, Bruce ; Lynch, Scott M.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Sociological Methods & Research (SMR) vol. 32 no. 03 (Feb. 2004), page 301-335.
Topik: statistics; Methodology; Evaluation; research
Fulltext: Lynch-301-35 - Bernard.pdf (216.38KB)

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Perpustakaan PKPM Nomor Panggil: S28 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

In sociological research, it is often difficult to compare non nested 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 specifically, as well as a Bayesian approach 10 modeling more generally, in tackling these issues. First, their 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 highlight the use of Bayesian posterior predictive distributions beyond these particular cases.

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