Differential Item Functioning (DIF) Testing with Estimation of the Latent Densities

差异项目功能 (DIF) 测试和潜在密度估计

• 批准号: 0818722
• 负责人: Carol Woods
• 金额: $ 6.7万
• 依托单位: Washington University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-15 至 2011-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0818722&HistoricalAwards=false
• 关键词: Differential; Item; Functioning; DIF; Testing

One important application of item response theory (IRT) is for identification of differential item functioning (DIF). DIF occurs when an item has different measurement properties for one group of people than another (e.g., men versus women), irrespective of group-mean differences on the latent variable. Typically, in IRT-based DIF testing, the latent variables are assumed to be normally distributed in the populations of people. However, this assumption may be untenable for some variables. The present research develops statistical methodology and software for IRT-based DIF testing in which the latent distribution for each group of people is estimated simultaneously with the item parameters.This research fills a gap in extant methodology and is aimed at improving the match between data and the statistical models used to assess DIF. Questionnaires measuring latent variables which are potentially nonnormally distributed are used as part of making, for example, psychological and medical diagnoses and treatment plans, and hiring or admission decisions in businesses or universities. Assessment instruments constructed based on majority-group individuals may provide misleading results for underrepresented groups. The proposed methodology could be applied in these areas to promote fair, accurate, and inclusive measurement. The research is supported by the Methodology, Measurement, and Statistics Program, the REESE Program, and a consortium of federal statistical agencies as part of a joint activity to support research on survey and statistical methodology.

项目反应理论（IRT）的一个重要应用是鉴别项目功能差异（DIF）。 DIF发生在项目对于一组人具有与另一组人不同的测量属性时（例如，男性与女性），无论潜在变量的组平均差异如何。 通常，在基于IRT的DIF测试中，假设潜在变量在人群中呈正态分布。 然而，这一假设对某些变量来说可能站不住脚。 本研究开发了基于IRT的DIF测试的统计方法和软件，其中每个群体的潜在分布与项目参数同时估计，本研究填补了现有方法的空白，旨在提高数据与用于评估DIF的统计模型之间的匹配。 测量潜在非正态分布的潜在变量的测量工具被用作制定例如心理和医学诊断和治疗计划以及企业或大学的招聘或录取决定的一部分。 根据多数群体的个人构建的评估工具可能会对代表性不足的群体提供误导性的结果。 拟议的方法可以应用于这些领域，以促进公平，准确和包容性的测量。 这项研究得到了方法、测量和统计方案、REESE方案和联邦统计机构联盟的支持，作为支持调查和统计方法研究的联合活动的一部分。