The purpose of this study is to apply the methods of factor․correlation․radial․multidimensional parceling to multidimensional scales in Confirmatory Factor Analysis and Structural Equation Model, and then investigate the possibility of the utility of item parceling method by comparing the results of the individual item method with the results of item parceling method. The item parceling method, defined as the sum or mean scores of individual item scores, have been widely used as observation variable in setting up the measurement model in CFA and SEM. The item parceling method is used in data: (1) that is not optimal(nonnormality); (2) that the sample size is small; (3)that has many items in factor; (4) that has hierarchical and complex factors in scale; and (5) that use the standardized scale which is failed to test CFA. The merits of item parceling method are; (1) the alleviation of non normality of data; (2) the simplicity of model; (3) the diminution of measure error index; (4) the increasing of communality; (5) the diminution of unique variance; (6) the stability of model fit; and (7) the stability of parameter estimates. The dispute of item parceling method is the assumption of unidimension and the results of stability or deviation of parameter estimate and model fit in simulation research. The model of research in this study are as follows. The CFA is testified in the model; (1) which has small factors in scale; (2) which has many hierarchical factors in scale; (3) which has small subject; (4) which has many and complex factors and items in standardized scale, and the SEM is testified in the model which has multidimensional factors. The item parceling methods which are composed of factor․correlation․radial․multidimensional method and the individual item method are applied to the measurement variables in models which are explained. The results are as follows. First, the item parceling method is more effective than individual item method in CFA. For example, the indexes of normality, model fit as χ2 , TLI, CFI, and RMSEA, parameter estimate, and convergent validity as construct reliability and AVE in item parceling method are more stable. Second, the item parceling method is more effective than individual item method in SEM. For example, the indexes of model fit and parameter estimate in item parceling method are more stable. Third, the most effective item parceling method in CFA is radial parceling method and in CFA is multidimensional parceling method. Forth, the item parceling method is effective as it is applied in the model that has small subject. Fifth, the item parceling method is effective as it is applied in the model that has many, complex, and standardized items. Sixth, the item parceling method is more effective than individual item method in SEM. This study suggests the theory of item parceling method from the point of view in psychological measurement and structure equation, the variable methods of item parceling, the merits of item parceling, and the differences between item parceling method and individual item method from empirical research results. This study makes the suggestions that item parceling method can perform to its potential when; (1) the subject size is small; (2) the psychometric properties of the given data is nonnormality; (3) model is complex, (4) there are violations of the assumptions for SEM(e.g., correlated errors), and that item parceling method should not be used in the measurement model which is based on wrong theory and concept.