Abstract
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 “best” approximating 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.
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© 1998 Springer-Verlag Berlin · Heidelberg
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Bozdogan, H., Shigemasu, K. (1998). Bayesian Factor Analysis Model and Choosing the Number of Factors Using a New Informational Complexity Criterion. In: Rizzi, A., Vichi, M., Bock, HH. (eds) Advances in Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-72253-0_45
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DOI: https://doi.org/10.1007/978-3-642-72253-0_45
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