Score-Based Tests of Measurement Bias in Explanatory Item Response Models

大规模、标准化的能力测试在社会中发挥着突出的作用，影响着大学录取、职业决策和资源分配。这项研究项目将涉及开发新的统计方法，使其更容易确定组成测试的项目是否公平。如果一项测试（或测试中的特定项目）不公平地使一组学生比其他学生更有优势，那么一些来自弱势群体的学生可能会错过他们根据自己的能力应得的机会。因此，确保标准化考试对参加考试的不同群体的学生公平是很重要的。新方法将在自由软件中实现，项目产生的所有数据将通过互联网公开传播。该项目还将支持一名心理测量学的博士生，这是一门STEM学科，有记录显示学生短缺。该项目将开发用于项目响应模型的统计方法。项目反应模型被认为是教育测试开发和分析的最先进的方法。新方法涉及统计学家所熟知的分数测试（也称为拉格朗日乘数测试）的推广。这些概括在心理测量学中相对未被探索，因此本项目中开发的方法将解决与测试公平性研究相关的未解决问题。特别是，这些新方法将允许人们使用比传统方法所需的更简单的统计模型来研究新的公平假设。新方法将进一步允许在许多学生群体和大型项目反应模型中研究公平性，其中许多模型比传统模型更复杂。随着理论的发展和软件的实现，该项目将通过仿真来说明方法的能力。模拟将直接比较新方法与传统方法，并将多个新统计数据相互比较。该项目将为研究人员提供研究测试公平性的新方法，提供执行方法的免费软件，以及指导研究人员优化使用方法的仿真结果。

Large-scale, standardized ability tests have a prominent role in society, impacting college admissions, occupational decisions, and resource distribution. This research project will involve the development of novel statistical methods that make it easier to determine whether or not the items making up a test are fair. If a test (or specific items on a test) were to unfairly advantage one group of students over others, then some students from the disadvantaged groups may miss out on the opportunities that they deserve based on their abilities. Thus, it is important to ensure that standardized tests are fair to the diverse groups of students taking the tests. The new methods will be implemented in free software, and all data resulting from the project will be openly disseminated via the internet. The project also will support a doctoral student in psychometrics, which is a STEM discipline with a documented shortage of students.This project will develop statistical methods that are designed to be used with item response models. Item response models are considered to be state-of-the-art methodology for educational test development and analysis. The new methods involve generalizations of the score test (also known as the Lagrange multiplier test) that is well known to statisticians. These generalizations have been relatively unexplored in psychometrics, so that the methods developed in this project will address unresolved problems related to the study of test fairness. In particular, these new methods will allow one to study novel hypotheses of fairness using simpler statistical models than are required for traditional methods. The new methods will further allow for the study of fairness across many groups of students and within a large class of item response models, many of which are more complex than traditional models. Along with theoretical development and software implementation, the project will illustrate the methods' abilities via simulation. The simulations will directly compare the new methods to traditional methods and compare multiple novel statistics to one another. The project will provide researchers with novel methods to study test fairness, free software to carry out the methods, and simulation results that guide researchers in the methods' optimal uses.