Abstract
Application of AIC to the number of factors problem in maximum likelihood factor analysis was investigated. Analysis of some empirical data sets suggested that nonconvergent cases and improper solutions require special considerations. Monte Carlo experiment showed that selecting the model minimizing the value of AIC with proper solution is quite satisfactory. However, there remains a requirement on sample size corresponding to the model characteristics such as communalities so that the occurrence of nonconvergent cases and improper solutions may be suppressed when the extracted number of factors is equal to the true one.
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