1997 Volume 24 Issue 2 Pages 147-158
This paper proposes a noniterative estimation procedure for confirmatory factor analysis based on an instrumental variable method. The parameters in this kind of model are typically fitted by the maximum likelihood, or the generalized least squares. However, these methods often require considerable time to compute the estimates, because the solutions generated by these estimation procedures are calculated by iterative minimization methods. The instrumental variable methods are of interest because their estimates can be obtained from explicit matrix formulas. They have the advantage compared with previous noniterative methods that linear equality constraints between unique and common factor variances are available. The constraints are useful for describing the reliability of psychological tests. The procedure is empirically compared to other methods. The conclusion, based on the data used in this study, is that the method described seems to work well.