Balanced scale is designed to measure a bipolar underlying construct. The item content of balanced scale is positively or negatively polarized. The purpose of mixing two kinds of items in a scale is to control the method effect associated with item wording. Such method effect is thought of as a major resource of common method variance and potentially threatens to the construct validity of balanced scale. In the framework of confirmatory factor analysis , various of models have been proposed to make a psychometric explanation of underlying construct of balanced scale as a single psychological construct plus method effect associated with item wording. The common models are the correlated trait-correlated method model (CTCM), correlated trait-correlated method minus one model (CTC(m-1)), bi-factor model (BIF). When fitting data, the models that has excellent fit indices are always chosen as the optimal models by researchers. Besides the fit indices, the correlation coefficients of items measured same construct using different methods should be greater than items measured different constructs using same method to support the construct validity. Unfortunately, this criterion is always ignored by some previous researchers. In their studies, the optimal model, such as CTCM, BIF, the factor loadings showed that some of items were strongly influenced by method effect rather than trait. To remedy the limitations of the extant models, a new model named random intercept factor analysis model was proposed to control the method effect associated with item wording. In such model, item is loaded on two latent variables, one represented the latent target trait and the other represented the response bias that is irrelevant with the latent target trait. Taking the Chinese version of Rosenberg Self-Esteem Scale-Revised (RSES-R) as an example, the current study aimed to test the applicability of the random intercept model in statistical control of the method effect associated with item wording. The results showed that the fit indices of random intercept model were only inferior to BIF. But given that (1) the ratio of the trait variance and method effect variance was reasonable; (2) the trait factor loading was significantly greater than the method factor loading; (3) extremely high correlation between the self-esteem factor score estimated by such model and the total score of the RSES-R; the random intercept model showed more reasonable and explicable than any other models. Additionally, based on the Over-Claiming Questionnaire, the indices of knowledge accuracy (d') and response bias (criterion location, c) were calculated. The correlation between the method factor score estimated by random intercept model and the d' was no-significant at 5% level, suggesting that such systematic error was not associated with a person's general cognitive ability. The correlation between the method factor score estimated by random intercept model and the c was positive, significant at 5% level, suggesting that the method effect associated with item wording shared common components with social desirability. In short, the evidences mentioned above support the validation of the random intercept facto analysis model for statistical control of the method effect associated with item wording.