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Longitudinal Analysis of Patient-Reported Outcomes in Clinical Trials: Applications of Multilevel and Multidimensional Item Response Theory
Psychometrika ( IF 3 ) Pub Date : 2021-06-17 , DOI: 10.1007/s11336-021-09777-y
Li Cai 1, 2 , Carrie R Houts 2
Affiliation  

With decades of advance research and recent developments in the drug and medical device regulatory approval process, patient-reported outcomes (PROs) are becoming increasingly important in clinical trials. While clinical trial analyses typically treat scores from PROs as observed variables, the potential to use latent variable models when analyzing patient responses in clinical trial data presents novel opportunities for both psychometrics and regulatory science. An accessible overview of analyses commonly used to analyze longitudinal trial data and statistical models familiar in both psychometrics and biometrics, such as growth models, multilevel models, and latent variable models, is provided to call attention to connections and common themes among these models that have found use across many research areas. Additionally, examples using empirical data from a randomized clinical trial provide concrete demonstrations of the implementation of these models. The increasing availability of high-quality, psychometrically rigorous assessment instruments in clinical trials, of which the Patient-Reported Outcomes Measurement Information System (PROMIS®) is a prominent example, provides rare possibilities for psychometrics to help improve the statistical tools used in regulatory science.



中文翻译:

临床试验中患者报告结果的纵向分析:多水平和多维项目反应理论的应用

随着药物和医疗器械监管审批流程的数十年先进研究和最新发展,患者报告结果 (PRO) 在临床试验中变得越来越重要。虽然临床试验分析通常将来自 PRO 的分数视为观察变量,但在分析临床试验数据中的患者反应时使用潜在变量模型的潜力为心理测量学和监管科学提供了新的机会。提供了一个易于理解的分析概述,这些分析通常用于分析心理测量学和生物测量学中熟悉的纵向试验数据和统计模型,例如增长模型、多级模型和潜在变量模型,以引起人们对这些模型之间的联系和共同主题的关注。在许多研究领域发现了用途。此外,使用来自随机临床试验的经验数据的示例提供了这些模型实施的具体演示。在临床试验中越来越多的高质量、心理测量学上严格的评估工具的可用性,其中患者报告的结果测量信息系统 (PROMIS®) 是一个突出的例子,为心理测量学提供了罕见的可能性,以帮助改进监管科学中使用的统计工具.

更新日期:2021-06-18
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