【摘要】：雙因子模型可以同時包含一個全局因子和多個局部因子,在描述多維測驗結構時有其獨特優(yōu)勢,近些年應用越來越廣泛。文章基于雙因子模型,提出了4種合成總分和維度分的方法,分別是:原始分法,加和法,全局題目加權加和法和局部題目加權加和法,并采用模擬的方法,在樣本量、測驗長度、維度間相關變化的條件下考察了這些方法與傳統(tǒng)多維IRT方法的表現(xiàn)。最后,通過實證研究對結果進行了驗證。結果顯示:(1)全局加權加和法和局部加權加和法,尤其是局部加權加和法合成的總分和維度分與真值最接近、信度最高。(2)在維度間相關較高,測驗長度較長的條件下,局部加權加和法的結果較好,部分條件下甚至優(yōu)于多維IRT法。(3)僅有局部加權加和法合成的維度分能夠反應維度間真實的相關關系。
[Abstract]:The two-factor model can include both a global factor and a number of local factors. It has its unique advantages in describing the multi-dimensional test structure and has been used more and more widely in recent years. Based on the two-factor model, four methods of synthesizing total score and dimension score are proposed in this paper. They are the original method, the addition method, the global topic weighted addition method and the local topic weighted sum method, and the simulation method is used in the sample size. The performance of these methods and the traditional multidimensional IRT method was investigated under the condition of the variation of the test length and the correlation between dimensions. Finally, the results are verified by empirical research. The results showed that: (1) the total score and dimension score of global weighted sum method and local weighted summation method, especially the local weighted summation method, were the closest to the true value, and the reliability was the highest. (2) the correlation between the two dimensions was higher. When the length of the test is longer, the results of the local weighted summation method are better than that of the multidimensional IRT method. (3) only the dimension points synthesized by the local weighted addition method can reflect the true correlation between the dimensions.
【作者單位】： 北京師范大學心理學部;
【基金】：國家自然科學基金(31571152) 北京市與中央在京高校共建項目(019-105812) 未來教育高精尖創(chuàng)新中心、中央高校基本科研業(yè)務費專項資金資助
【分類號】：B841.7

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