This research develops a new method for analyzing relation for factors which combines graphical modeling (GM) and factor analysis. In this method, estimation of the inverse of the variance-covariance matrix is done in the framework of factor analysis, and then the data-model fit is investigated using GM. The partial correlation coefficients of the estimated model are calculated, and the estimation of parameters is repeated until discovery of the worst fit index. In order to confirm the effectiveness of this method, three correlation matrices were analyzed as a real data study. In first and second case, intelligence models of Harman and Turstone were restructured using this method. In third case, EQ model was structured using it. The results show that this method can be apply GM for latent variables and a good assistant to set up path models for factors.
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