The use and interpretation of educational and psychological test scores are paramount to individual outcomes and opportunities. Methods for detecting differential item functioning (DIF) are imperative for item analysis when developing and revising assessments, particularly as it pertains to fairness across populations, languages, and cultures. We discuss the practical application of third generation of DIF, which proposes an ecological framework for explaining why DIF occurs using sociological, community, and contextual variables as possible explanations of item responding. We examined school district clusters for DIF through a model-based approach via multilevel logistic regression random-intercept and random-coefficient models to detect racial/ethnic DIF on a youth risk and needs assessment. We demonstrate how the use of district-level administrative data as estimates of student's contextual environments shows promise to understand ecological sources of DIF and DIF variance. The implication of the work progresses DIF research, enhances the approach to understanding item responses, and provides a more accurate understanding of youth development through an ecological framework. Recommendations for practice and future studies are discussed.

中文翻译：

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青年风险和需求评估背景下项目响应的生态框架

教育和心理测试分数的使用和解释对个人结果和机会至关重要。在开发和修改评估时，检测差异项目功能 (DIF) 的方法对于项目分析是必不可少的，特别是因为它涉及跨人口、语言和文化的公平性。我们讨论了第三代 DIF 的实际应用，它提出了一个生态框架来解释 DIF 发生的原因，使用社会学、社区和上下文变量作为项目响应的可能解释。我们通过基于模型的方法通过多级逻辑回归随机截距和随机系数模型检查学区集群的 DIF，以检测青年风险和需求评估中的种族/族裔 DIF。我们展示了使用地区级行政数据作为学生情境环境的估计如何显示出理解 DIF 和 DIF 方差的生态来源的前景。这项工作的意义推进了 DIF 研究，增强了理解项目反应的方法，并通过生态框架提供了对青年发展的更准确的理解。讨论了实践和未来研究的建议。