Using Logistic regression to assess Differential Item Functioning in Polytomous Items / Logistic迴歸在檢測多分題差異試題功能之效果

碩士 / 國立中正大學 / 心理學研究所 / 92 / Studies of detecting differential item functioning (DIF) in polytomous items have gained much attention in recent years. This study compares two methods of detecting DIF in polytomous items under various simulated conditions: logistic discriminate function analysis (LDFA; Miller & Spray, 1993) and common slope multinomial logistic regression (MLR; French & Miller, 1996; Hidalgo-Montesinos & Gomez-Benito, 2003). Experiment 1 focuses on the graded response model (GRM) and Experiment 2 on the partial credit model (PCM). The dependent variable are empirical Type I error rate and statistical power. One hundred replications were made under each condition.
The results show that both methods performed better under the PCM than the GRM, when tests contained solely polytomous items than when tests contained both dichotomous and polytomous items, when the DIF patterns were nonuniform than they were uniform. When tests contained solely polytomous items, LDFA yielded slightly better results than MLR. When tests contained both dichotomous and polytomous items, they performed similarly. Therefore, LDFA is recommended when tests contain solely polytomous items (e.g., Likert-type or rating scale items) and both methods are recommended when tests contain both dichotomous and polytomous items.

Identiferoai:union.ndltd.org:TW/092CCU00071027
Date January 2004
Creators鄭致寯
ContributorsWen-Chung Wang, 王文中
Source SetsNational Digital Library of Theses and Dissertations in Taiwan
Languagezh-TW
Detected LanguageEnglish
Type學位論文 ; thesis
Format144

Page generated in 0.0015 seconds