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Choosing the number of factors in factor analysis with incomplete data via a hierarchical Bayesian information criterion
The Bayesian information criterion (BIC), defined as the observed data log likelihood minus a penalty term based on the sample size $N$, is a popular model selection criterion for factor analysis with complete data.
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