Examining Validity Evidence of Self-Report Measures Using Differential Item Functioning: An Illustration of Three Methods

IF 2 3区 心理学 Q2 PSYCHOLOGY, MATHEMATICAL
A. Gadermann, Michelle Y. Chen, S. D. Emerson, B. Zumbo
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引用次数: 8

Abstract

The investigation of differential item functioning (DIF) is important for any group comparison because the validity of the inferences made from scale scores could be compromised if DIF is present. DIF occurs when individuals from different groups show different probabilities of selecting a response option to an item after being matched on the underlying latent variable that the item is supposed to measure. The aim of this paper is to inform the practice of DIF analyses in survey research. We focus on three quantitative methods to detect DIF, namely nonparametric item response theory (NIRT), ordinal logistic regression (OLR), and mixed-effects or multilevel models. Using these methods, we demonstrate how to examine DIF at the item and scale levels, as well as in multilevel settings. We discuss when these techniques are appropriate to use, what data assumptions they have, and their advantages and disadvantages in the analysis of survey data.
利用差异项函数检验自我报告测量的有效性证据——三种方法的例证
差异项目功能(DIF)的调查对于任何小组比较都很重要,因为如果存在DIF,从量表得分得出的推论的有效性可能会受到影响。当来自不同群体的个体在与项目应该测量的潜在变量匹配后,表现出选择对项目的响应选项的不同概率时,就会发生DIF。本文的目的是为DIF分析在调查研究中的实践提供信息。我们重点研究了三种检测DIF的定量方法,即非参数项目反应理论(NIRT)、有序逻辑回归(OLR)和混合效应或多水平模型。使用这些方法,我们演示了如何在项目和规模级别以及多级别设置中检查DIF。我们讨论了这些技术何时适合使用,它们有什么数据假设,以及它们在调查数据分析中的优缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.70
自引率
6.50%
发文量
16
审稿时长
36 weeks
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