Measurement Error in Latent Class Models of Adherence

依从性的潜在类别模型中的测量误差

• 批准号: 7540950
• 负责人: Knashawn Hodge Morales
• 金额: $ 13.78万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7540950
• 关键词: Accounting; Adherence; Affect; Age; Antidepressive Agents; Area; Award; Cardiovascular Diseases; Clinical assessments; Data; Development; Elderly; Epidemiologic Studies; Equation; Funding; Future; Gender; Goals; Growth; Guidelines; Health Services Research; Heterogeneity; Hybrids; Intervention; Intervention Studies; Investigator-Initiated Research; Knowledge; Lead; Learning; Literature; Measurement; Measures; Mental Health Services; Mental disorders; Mentored Research Scientist Development Award; Mentors; Methodology; Methods; Modeling; National Institute of Mental Health; Outcome; Patient Self-Report; Patients; Pattern; Phase; Phase I Clinical Trials; Primary Health Care; Race; Randomized; Randomized Controlled Clinical Trials; Relative (related person); Research; Research Methodology; Sampling; Scientist; Screening procedure; Site; Statistical Methods; Structural Models; Suicide prevention; System; Treatment Effectiveness; United States National Institutes of Health; Validation; base; career; career development; collaborative trial; depression; design; education planning; effective therapy; effectiveness trial; experience; follow up assessment; method development; non-compliance; pill; response; tool; treatment as usual; treatment effect

DESCRIPTION (provided by applicant): This application for an NIMH Mentored Research Scientist Career Development (K01) award entitled "Measurement error in latent class models of adherence" seeks support to provide an intensive, mentored research experience, culminating in a successful investigator-initiated research award application and launching a career as an academic biostatistician focusing on developing statistical methods for difficult methodological problems affecting the validity of mental health services research. As part of the education plan, the PI will increase her understanding of mental disorders and the systems used to collect services research data and explore a new area of statistical methods (latent class and latent variable methods). The four-phase research plan focuses on measurement error, latent class and latent variable methods for research questions generated from the NIMH study of "Prevention of Suicide in Primary Care Elderly: Collaborative Trial," but apply to data from randomized trials in general. The conventional "measurement models" under the SEM framework do not naturally accommodate validation data from a sub-sample. The classical and Berkson measurement models that appear in the statistical literature, offer different ways of incorporating validation data as a measurement error variance estimate like a variance component. The goals of the K and my future research focuses on incorporating these different measurement error approaches. Phase 1 is designed to understand how patterns of adherence are related to depression trajectories and how the tow influence treatment effects. This phase will focus on generating knowledge of latent class and latent variable methodology with application to the PROSPECT study. Phase 2 focuses on estimating measurement error in the measures of adherence. Phase 3 uses results from Phases 1 and 2 to adjust latent class/variable results for error in the measurement of adherence. Phase 4 will use everything learned in Phase 1, 2, and 3 to guide the development of a NIH R01 for statistical methods that accurately accommodate measurement error. In addition, Bayesian model averaging is proposed to account for model error by eliminating the choice of the number of latent classes. This research plan will provide useful tools that will aid in the design and analysis of other mental health services studies.

描述（由申请人提供）：NIMH指导研究科学家职业发展（K01）奖的题为“依从性潜在阶级模型的测量错误”的申请寻求支持，以提供丰富的，有指导的研究经验，最终在成功的研究人员宣传的研究奖励应用程序中，将职业置于研究方面的研究方面的研究方面，对发展的态度进行了统计学上的研究，该奖项的培养范围是对型号的培养方法的关注。作为教育计划的一部分，PI将增加她对精神障碍的理解，以及用于收集服务研究数据的系统并探索统计方法的新领域（潜在类和潜在可变方法）。四相研究计划的重点是测量误差，潜在类别和潜在可变方法，用于NIMH研究“预防初级保健老年人自杀：协作试验”的研究问题，但适用于总体上随机试验的数据。 SEM框架下的常规“测量模型”并不自然地适合子样本中的验证数据。出现在统计文献中的经典和Berkson测量模型，提供了将验证数据合并为测量误差方差估算的不同方法，例如方差组件。 K和我未来的研究的目标重点是纳入这些不同的测量误差方法。第1阶段旨在了解依从性模式与抑郁轨迹的粘附方式以及拖曳如何影响治疗效果有关。该阶段将着重于在潜在研究中应用潜在类别和潜在变量方法的知识。第2阶段的重点是估计依从性测量的测量误差。第3阶段使用第1阶段和第2阶段的结果来调整潜在的类/变量结果，以确保依从性测量。第4阶段将使用第1、2和3阶段中学到的所有内容来指导NIH R01的开发，以准确适应测量误差的统计方法。此外，提出了贝叶斯模型平均，以通过消除潜在类数量的选择来解决模型错误。该研究计划将提供有用的工具，以帮助对其他心理健康服务研究的设计和分析。