Even though the structural equation modeling has been used often by the researchers, it is observed that the assumptions are not examined before the analysis, the appropriate parameter estimation method was not performed. In cases when the estimations are not met in structural equation modeling, estimates below or above the parameter values are conducted. In this study, it is aimed at investigating the fit indexes of the model, estimated with a different parameter estimation method and sample size, based on item subtraction and restricted parameters (1, CTT and IRT values) in the confirmatory factor analysis model with multicollinearity problem. As a result of the estimation, the model was detected to make biased estimations when multicollinearity and sample size assumptions are not met. In order to prevent item loss, item parameters are suggested to be restricted with the values estimated from the classical test theory and item response theory. Based on the results of this research, it is asserted that all assumptions, as well as sample size and multicollinearity problem, are required to be examined before the confirmatory factor analysis is estimated. Otherwise there may be biased predictions. One of the multicollinearity problem-causing items may be subtracted or the items may be integrated. In order for the item not to be lost, the item parameters may be restricted. As information is obtained before the items, the values predicted with the classical test theory may be used in parameter restriction instead of 0 or 1.

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