Evaluating item fit for multidimensional item response models

被引:17
|
作者
Zhang, Bo [1 ]
Stone, Clement A. [2 ]
机构
[1] Univ Wisconsin, Dept Educ Psychol, Milwaukee, WI 53201 USA
[2] Univ Pittsburgh, Pittsburgh, PA 15260 USA
关键词
multidimensional item response theory; MIRT; model data fit; item fit; type I error; power;
D O I
10.1177/0013164407301547
中图分类号
G44 [教育心理学];
学科分类号
0402 ; 040202 ;
摘要
This research examines the utility of the s-chi(2) statistic proposed by Orlando and Thissen ( 2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test structures: approximate simple structure and complex structure. Overall, results show that this statistic is capable of evaluating item fit in the application of multidimensional item response models. It is important to identify the structure of multidimensional tests before this fit statistic is applied. For tests with an approximate simple structure, the sampling distribution can be approximated by a standard chi-square distribution. But for tests with a complex structure, that approximation is more complicated. As regards power in detecting the model nonfitting items, the performance of this statistic in multidimensional tests is comparable to that in unidimensional tests.
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页码:181 / 196
页数:16
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