Collaborative Research: Longitudinal Diagnostic Models

合作研究：纵向诊断模型

• 批准号: 1030337
• 负责人: Jonathan Templin
• 金额: $ 7.66万
• 依托单位: University of Georgia Research Foundation Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-15 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1030337&HistoricalAwards=false
• 关键词: Collaborative; Research; Longitudinal; Diagnostic; Models

Diagnostic modeling, also known as cognitive diagnosis, is a field of psychometrics that has seen increased research activity in recent years due to the potential for diagnosing the mental states of individuals, such as in the social sciences (e.g., criteria indicating psychological disorders) or in education (e.g., the skills examinees may possess). To date, such models have been developed and expanded for use in a broad spectrum of research areas and have been shown to be effective at classifying individuals on a set of categorical latent variables. Although the development of diagnostic models has focused on more comprehensive and flexible measurement models for data collected at a single occasion, there have been no systematic efforts to extend these models into the measurement of individual change. Simply put, the researcher who wishes to study changes in diagnostic status over time currently cannot do so. This research project will focus on the development, evaluation, and utilization of longitudinal extensions of diagnostic models for the measurement of change over time. In developing longitudinal diagnostic models, advances must be made that balance the model demands of potentially large numbers of parameters with practical and accurate approximations. The investigators will develop practical and feasible longitudinal methods for diagnostic measurement, modeling, and assessment, and they will examine their accuracy, sensitivity, and comparative efficiency. The investigators also will examine the practical considerations and statistical issues in applying these methods in real-world longitudinal diagnostic analyses. Freely available software will be provided for researchers and practitioners to utilize these methods in their own studies. This project will expand the practicality of diagnostic models and add to the number of research and real-world scenarios where such models can be used. The models and software developed from this project will fill an existing void that has limited the study of diagnostic phenomena over time. Furthermore, guidelines about the structure of data needed for each model (i.e., sample size or number of measurement occasions) will allow for application of such models across a wide spectrum of empirical research areas studying how behavioral phenomena change over time. The methods developed from this project will enable a more rigorous examination of how mental states change over time. The results of this research have the potential to greatly advance basic understanding of how people develop and change with respect to diagnostic attributes and clinical criteria.

诊断建模，也称为认知诊断，是近年来由于诊断个体的精神状态的潜力而增加的研究活动的心理测量学领域，例如在社会科学中（例如，指示心理障碍的标准）或在教育中（例如，考生可能具备的技能）。 到目前为止，这种模型已经开发和扩展，用于广泛的研究领域，并已被证明是有效的分类个人的一组分类潜变量。 虽然诊断模式的发展集中在更全面和更灵活的测量模式，在一个单一的场合收集的数据，一直没有系统的努力，这些模式扩展到个人变化的测量。 简而言之，希望研究诊断状态随时间变化的研究人员目前无法做到这一点。 该研究项目将侧重于开发，评估和利用诊断模型的纵向扩展，以测量随时间的变化。 在开发纵向诊断模型时，必须取得进展，以平衡模型对潜在大量参数的需求与实际和准确的近似值。 研究人员将开发实用可行的诊断测量，建模和评估的纵向方法，并检查其准确性，灵敏度和相对效率。 研究人员还将研究在现实世界的纵向诊断分析中应用这些方法的实际考虑和统计问题。 将向研究人员和从业人员免费提供软件，供他们在自己的研究中利用这些方法。该项目将扩大诊断模型的实用性，并增加可以使用这些模型的研究和现实世界场景的数量。 从这个项目开发的模型和软件将填补现有的空白，限制了诊断现象的研究随着时间的推移。 此外，关于每个模型所需数据结构的准则（即，样本量或测量次数）将允许在广泛的实证研究领域应用这些模型，研究行为现象如何随时间变化。 从这个项目中开发的方法将能够更严格地检查精神状态如何随着时间的推移而变化。 这项研究的结果有可能大大推进人们如何发展和变化方面的诊断属性和临床标准的基本理解。