Bayesian Analysis of Structural Equation Modeling

Kazuo Shigemasu, Takahiro Hoshino and Takuya Ohmori
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Kazuo Shigemasu: University of Tokyo
Takahiro Hoshino: University of Tokyo
Takuya Ohmori: University of Tokyo

A chapter in Measurement and Multivariate Analysis, 2002, pp 207-216 from Springer

Abstract: Summary A Bayesian procedure to make exact distributional inferences about all structural parameters and latent variables was proposed. This procedure handles the problem associated with the fixed parameters by means of conditinalization, and uses the Gibbs sampler to derive the posterior distribution for each unknown quantitiy. A simulation study was conducted to evaluate the performance of the proposed procedure.

Keywords: Structural Equation Model; Posterior Distribution; Prior Distribution; Factor Score; Gibbs Sampler (search for similar items in EconPapers)
Date: 2002
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-4-431-65955-6_22

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DOI: 10.1007/978-4-431-65955-6_22

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