On Bayesian estimation in unrestricted factor analysis |
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| Authors: | Raymond F Koopman |
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| Institution: | (1) Psychology Dept., Simon Fraser University, V5A 1S6 Burnaby, B.C., Canada |
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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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| Keywords: | communalities uniquenesses common variance unique variance Heywood cases unbiased estimates missing data |
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