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.

中文翻译：

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使用差异项功能检查自我报告措施的有效性证据

差异项功能（DIF）的调查对于任何组比较都是重要的，因为如果存在DIF，从量表分数得出的推论的有效性可能会受到损害。当来自不同组的个体在与该项目应衡量的潜在潜变量匹配后，显示出对该项目选择响应选项的可能性不同时，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参考。我们专注于三种检测DIF的定量方法，即非参数项响应理论（NIRT），有序逻辑回归（OLR）和混合效应或多级模型。使用这些方法，我们演示了如何在项目和比例级别以及多级别设置中检查DIF。我们讨论了何时适合使用这些技术，