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Bayesian Analysis of Structural Equation Modeling

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Book cover Measurement and Multivariate Analysis

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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.

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Author information

Authors and Affiliations

  1. University of Tokyo, 3-8-1 Komaba, Megroku, Tokyo, 153-8902, Japan

    Kazuo Shigemasu, Takahiro Hoshino & Takuya Ohmori

Authors
  1. Kazuo Shigemasu
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  2. Takahiro Hoshino
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  3. Takuya Ohmori
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Editor information

Editors and Affiliations

  1. Measurement and Evaluation Program CTL, OISE/UT, The University of Toronto, 252 Bloor Street West, M5S 1V6, Toronto, Ontario, Canada

    Shizuhiko Nishisato (Professor Emeritus) (Professor Emeritus)

  2. Center for Information on Statistical Sciences, The Institute of Statistical Mathematics, 4-6-7 Minami Azabu, 106-8569, Minato-ku, Tokyo, Japan

    Yasumasa Baba (Professor) & Koji Kanefuji (Associate Professor) (Professor) &  (Associate Professor)

  3. Information Complexity & Model Selection Department of Statistics, 336 SMC, The University of Tennessee, 37996-0532, Knoxville, TN, USA

    Hamparsum Bozdogan (McKenzie Professor in Business) (McKenzie Professor in Business)

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© 2002 Springer Japan

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Shigemasu, K., Hoshino, T., Ohmori, T. (2002). Bayesian Analysis of Structural Equation Modeling. In: Nishisato, S., Baba, Y., Bozdogan, H., Kanefuji, K. (eds) Measurement and Multivariate Analysis. Springer, Tokyo. https://doi.org/10.1007/978-4-431-65955-6_22

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  • DOI: https://doi.org/10.1007/978-4-431-65955-6_22

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-65957-0

  • Online ISBN: 978-4-431-65955-6

  • eBook Packages: Springer Book Archive

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