A Bayesian Approach to Nonlinear Latent Variable Models Using the Gibbs Sampler and the Metropolis-Hastings Algorithm.

Arminger, Gerhard; Muthen, Bengt O.

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Peer reviewed

ERIC Number: EJ574592

Record Type: Journal

Publication Date: 1998

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ISSN: ISSN-0033-3123

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A Bayesian Approach to Nonlinear Latent Variable Models Using the Gibbs Sampler and the Metropolis-Hastings Algorithm.

Arminger, Gerhard; Muthen, Bengt O.

Psychometrika, v63 n3 p271-300 Sep 1998

Nonlinear latent variable models are specified that include quadratic forms and interactions of latent regressor variable as special cases. To estimate the parameters, the models are put in a Bayesian framework with conjugate priors for the parameters. The proposed estimation methods are illustrated by two simulation studies. (SLD)

Descriptors: Algorithms, Bayesian Statistics, Estimation (Mathematics), Mathematical Models, Simulation

Publication Type: Journal Articles; Reports - Descriptive

Education Level: N/A

Audience: N/A

Language: English

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