An Investigation of Chi-Square and Entropy Based Methods of Item-Fit Using Item Level Contamination in Item Response Theory

被引：0

作者：

Dardick, William R. ^{[1
]}

Weiss, Brandi A. ^{[1
]}

机构：

[1] George Washington Univ, Washington, DC 20052 USA

来源：

JOURNAL OF MODERN APPLIED STATISTICAL METHODS | 2019年 / 18卷 / 02期

关键词：

Item response theory; IRT item-fit; IRT model fit; Monte Carlo simulation; entropy; GOODNESS-OF-FIT; THEORY MODELS; STATISTICS; SIMULATION;

D O I：

10.22237/jmasm/1604190480

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

New variants of entropy as measures of item-fit in item response theory are investigated. Monte Carlo simulation(s) examine aberrant conditions of item-level misfit to evaluate relative (compare EMRj, X-2, G(2), S-X-2, and PV-Q(1)) and absolute (Type I error and empirical power) performance. EMRj has utility in discovering misfit.

引用

页数：42

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