【摘要】：雙因子模型可以同時(shí)包含一個(gè)全局因子和多個(gè)局部因子,在描述多維測(cè)驗(yàn)結(jié)構(gòu)時(shí)有其獨(dú)特優(yōu)勢(shì),近些年應(yīng)用越來(lái)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(quán)加和法和局部題目加權(quán)加和法,并采用模擬的方法,在樣本量、測(cè)驗(yàn)長(zhǎng)度、維度間相關(guān)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(guò)實(shí)證研究對(duì)結(jié)果進(jìn)行了驗(yàn)證。結(jié)果顯示:(1)全局加權(quán)加和法和局部加權(quán)加和法,尤其是局部加權(quán)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(guān)較高,測(cè)驗(yàn)長(zhǎng)度較長(zhǎng)的條件下,局部加權(quán)加和法的結(jié)果較好,部分條件下甚至優(yōu)于多維IRT法。(3)僅有局部加權(quán)加和法合成的維度分能夠反應(yīng)維度間真實(shí)的相關(guān)關(guān)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(xué)心理學(xué)部;
【基金】：國(guó)家自然科學(xué)基金(31571152) 北京市與中央在京高校共建項(xiàng)目(019-105812) 未來(lái)教育高精尖創(chuàng)新中心、中央高校基本科研業(yè)務(wù)費(fèi)專(zhuān)項(xiàng)資金資助
【分類(lèi)號(hào)】：B841.7

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