Innovative Analytical Methods for Repeated Measures in the OHTS Study

OHTS 研究中重复测量的创新分析方法

基本信息

批准号：
10219276
负责人：
MAE O GORDON
金额：
$ 23.59万
依托单位：
WASHINGTON UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-08-01 至 2023-07-31
项目状态：
已结题

项目摘要

Clustered or longitudinal data are commonly encountered in ophthalmology studies. Naturally, left and right eyes of the same subject are paired and dependent. Also, in longitudinal ophthalmology studies, the multiple measures on the same subject tend to be correlated. These correlations (or the heterogeneity between different subjects) are usually described by two statistical models: fixed effects models and random effects models. However, both methods have their limitations. To achieve an appropriate balance between accuracy and efficiency, we propose a new approach in between the fixed effects and random effects models, assuming that the heterogeneity for each subject belongs to different groups. By penalizing the fusion effects (the differences between two subject-specific effects), we automatically group the subject-specific effects without knowing the group membership of the subjects in advance. We thus term our method as “fusion effects” models. We have three aims in utilizing the fusion effects model in longitudinal ophthalmology studies: (1) propose the estimation and inference methods for fusion effects models, with application to continuous (linear), binary (logistic), and time-to-event (Cox’s model) outcomes; (2) consider multiple fusion effects (e.g., fusion intercept and fusion slope) and multi-level fusion effects models; (3) develop and disseminate a user-friendly statistical software package that will enable researchers to implement these methods with ease. To illustrate our methods, we will use the Ocular Hypertension Treatment Study Phase I and II (OHTS), a longitudinal study with measures from both eyes of 1,636 participants followed from 1994 to 2009. The OHTS study has multiple types of outcomes and multi-level structure, which is an ideal study for the proposed research.

自然，在眼科研究中经常会遇到聚类或纵向数据。同一受试者的眼睛是成对且相互依赖的。此外，在纵向眼科研究中，多只眼睛是成对的且相互依赖的。对同一主题的测量往往是相关的。不同的受试者）通常由两种统计模型来描述：固定效应模型和随机效应然而，这两种方法都有其局限性，无法在准确性之间取得适当的平衡。和效率，我们提出了一种介于固定效应和随机效应模型之间的新方法，假设通过惩罚融合效应（融合效应），每个受试者的异质性属于不同的群体。两个特定于主题的效果之间的差异），我们自动对特定于主题的效果进行分组，而无需因此，我们提前了解受试者的群体成员身份，将我们的方法称为“融合效应”。我们在纵向眼科研究中利用融合效应模型有三个目标：（1）提出融合效应模型的估计和推理方法，应用于连续（线性），二元（逻辑）和事件发生时间（Cox 模型）结果；(2) 考虑多种融合效应（例如，融合） (3) 开发和传播方便用户的统计软件包将使研究人员能够轻松实施这些方法。为了说明我们的方法，我们将使用高眼压治疗研究 I 期和 II 期 (OHTS)， 1994 年至 2009 年间对 1,636 名参与者双眼进行测量的纵向研究。研究具有多种类型的结果和多层次的结构，这是拟议的理想研究研究。