Improving Measurement Precision of Test Batteries Using Multidimensional Item Response Models

Wen Chung Wang, Po Hsi Chen, Ying Yao Cheng

研究成果: 雜誌貢獻综述文章

82 引文 斯高帕斯(Scopus)


A conventional way to analyze item responses in multiple tests is to apply unidimensional item response models separately, one test at a time. This unidimensional approach, which ignores the correlations between latent traits, yields imprecise measures when tests are short. To resolve this problem, one can use multidimensional item response models that use correlations between latent traits to improve measurement precision of individual latent traits. The improvements are demonstrated using 2 empirical examples. It appears that the multidimensional approach improves measurement precision substantially, especially when tests are short and the number of tests is large. To achieve the same measurement precision, the multidimensional approach needs less than half of the comparable items required for the unidimensional approach.

頁(從 - 到)116-136
期刊Psychological Methods
出版狀態已發佈 - 2004 三月 1

ASJC Scopus subject areas

  • Psychology (miscellaneous)