Bayesian Analysis in Applications of Hierarchical Models: Issues and Methods.

Seltzer, Michael H.; And Others

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Peer reviewed

ERIC Number: EJ531743

Record Type: Journal

Publication Date: 1996

Pages: N/A

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ISSN: ISSN-1076-9986

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Bayesian Analysis in Applications of Hierarchical Models: Issues and Methods.

Seltzer, Michael H.; And Others

Journal of Educational and Behavioral Statistics, v21 n2 p131-67 Sum 1996

The Gibbs sampling algorithms presented by M. H. Seltzer (1993) are fully generalized to a broad range of settings in which vectors of random regression parameters in the hierarchical model are assumed multivariate normally or multivariate "t" distributed across groups. The use of a fully Bayesian approach is discussed. (SLD)

Descriptors: Algorithms, Bayesian Statistics, Estimation (Mathematics), Multivariate Analysis, Regression (Statistics), Sampling

Publication Type: Reports - Evaluative; Journal Articles

Education Level: N/A

Audience: N/A

Language: English

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Author Affiliations: N/A