Effects of Ignoring Item Interaction on Item Parameter Estimation and Detection of Interacting Items  

Oleh:

Chen, Cheng-Te ; Wang, Wen-Chung

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Applied Psychological Measurement vol. 31 no. 5 (Sep. 2007), page 388-411.
Topik: local item dependence; three-parameter logistic model; generalized partial credit model; posterior predictive check; item response theory; SAS NLMIXED
Fulltext: 388.pdf (258.47KB)

Isi artikel

This study explores the effects of ignoring item interaction on item parameter estimation and the efficiency of using the local dependence indexQ3 and the SAS NLMIXED procedure to detect item interaction under the three-parameter logistic model and the generalized partial credit model. Through simulations, it was found that ignoring positive item interaction led to overestimation for the discrimination parameters, underestimation for the difficulty parameters, and aQ3 much smaller than zero. As the guessing parameters approached zero, the overestimation for the discrimination parameters became more serious. In contrast, ignoring negative item interaction led to underestimation for the discrimination parameters, overestimation for the difficulty parameters, and aQ3 much larger than zero. As the guessing parameters approached zero, the underestimation for the discrimination parameters became less serious. A modification of posterior predictive p value forQ3 was proposed to detect item interaction and was found to work very well. Direct modeling of item interaction using NLMIXED was demonstrated.

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