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On Bayesian estimation in unrestricted factor analysis

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Abstract

It is shown that the common and unique variance estimates produced by Martin & McDonald's Bayesian estimation procedure for the unrestricted common factor model have a predictable sum which is always greater than the maximum likelihood estimate of the total variance. This fact is used to justify a suggested simple alternative method of specifying the Bayesian parameters required by the procedure.

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References

  • Clarke, M. R. B. A rapidly convergent method for maximum-likelihood factor analysis.British Journal of Mathematical and Statistical Psychology, 1970,23, 43–52.

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  • Martin, J. K., & McDonald, R. P. Bayesian estimation in unrestricted factor analysis: a treatment for Heywood cases.Psychometrika, 1975,40, 505–517.

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Authors and Affiliations

  1. Psychology Dept., Simon Fraser University, V5A 1S6, Burnaby, B.C., Canada

    Raymond F. Koopman

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  1. Raymond F. Koopman
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Koopman, R.F. On Bayesian estimation in unrestricted factor analysis. Psychometrika 43, 109–110 (1978). https://doi.org/10.1007/BF02294093

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  • DOI: https://doi.org/10.1007/BF02294093

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