关键词: 人格测验, 项目信息函数, 双参数逻辑斯谛模型

Abstract: With the development of psychological and educational measurement, item response theory (IRT) is being increasingly used in psychological and educational testing areas. There have been many large-scale tests based on IRT, such as TOEFL and GRE. Further, there have also been many studies on the applications of IRT in personality questionnaires. However, many problems still remain, including model selection and determining the appropriate numbers of parameters. It is vital to conduct empirical studies in order to discuss the probability of applying IRT to this area. The Chinese Soldier Personality Questionnaire (CSPQ) was used in this study in order to discuss the possibility of applying IRT to personality questionnaires with large samples.
In the study, 100,523 young individuals were tested using the computerized CSPQ. Subjects whose standard score in every subtest was less than 70 were considered to be normal, while the others were disqualified. Further, structural interviews were conducted by psychological experts in order to confirm the symptoms of those disqualified. If they indeed exhibited some symptoms, they were placed in the disqualified group. Additionally, 221 schizophrenia patients were tested using the same questionnaire, and they were placed in the schizophrenia group. From among the normal subjects, 2676 were randomly selected and placed in the normal group. The SPSS 11.5 software was used to test the unidimensionality of every subtest. Moreover, the BILOG-MG software was used to analyze the data with the two-parameter logistic model (2PL) based on IRT.
Items with discriminating parameters beyond the range of (0.3, 4) were deleted as they provided little information that was relevant to testing. Moreover, before and after deleting these items, there was no noticeable change in the maximum test information and the correlations between IRT scores and standard scores. In the case of the standard scores, the distributions of the schizophrenia group were similar to those of the normal group, while in the case of the IRT scores, the distributions of the schizophrenia group moved towards those of the disqualified group.
As shown in this study, IRT can improve the efficiency of testing with nearly the same precision. Further, IRT is more suitable for identifying the differences between varied groups, which is another advantage of IRT analysis. Therefore, as a new testing theory, IRT can and should be used in the analysis of personality questionnaires. However, personality questionnaires are not the same as cognitive tests, and different models of IRT (for example, nonparametric models) have not been compared in this study. Therefore, the best model for personality questionnaires should be discussed further

Key words: Personality testing, Item information function, Two-parameter logistic model