Bayesian Factor Analysis Model and Choosing the Number of Factors Using a New Informational Complexity Criterion

  • Hamparsum Bozdogan
  • Kazuo Shigemasu
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)


This paper introduces two forms of informational complexity ICOMP criteria of Bozdogan (1988, 1990,1994) as a decision rule for model selection and evaluation in Bayesian Confirmatory Factor Analysis (BAYCFA) model due to Press and Shigemasu (1989) in contemporaneously choosing the number of factors and determining the “bestapproximating factor pattern structure. A Monte Carlo simulation example with a known factor pattern structure and known actual number of factors is shown to demonstrate the utility and versatility of the new approach in recovering the true structure.

Key words

Bayesian Confirmatory Factor Analysis Choosing the Number of Factors Informational Complexity 


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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Hamparsum Bozdogan
    • 1
  • Kazuo Shigemasu
    • 2
  1. 1.Department of StatisticsThe University of TennesseeKnoxvilleUSA
  2. 2.Department of Life SciencesThe University of TokyoTokyo 153Japan

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