Design and Analysis of Multiphase Studies Featuring Incomplete Data

不完整数据的多相研究的设计和分析

• 批准号: RGPIN-2017-04207
• 负责人: Cook, Richard
• 金额: $ 4.08万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=710932
• 关键词: Design; Analysis; Multiphase; Studies; Featuring

Response-Dependent Two-Phase Designs for Dynamic Processes I will develop innovative ways of selecting individuals for biomarker sub-studies in large cohorts aimed at examining the relationship between genetic and serum biomarkers to longitudinal responses which may involve repeated measures and time-to-event data. Phase I samples involve the collection of longitudinal or life history data along with specimens stored in biobanks. Phase II samples are defined by the set of individuals for whom the stored specimens are assayed and can then be used in analyses. Algorithms for the optimal selection of Phase II samples will be developed based on large sample theory with different selection models obtained depending on the framework for the longitudinal analysis (i.e. marginal analyses, hierarchical mixed effect models, transition models). Methods for the secondary analysis of data from case-cohort designs will also be developed using likelihood and weighted estimating functions to correct for biased samples. The case-cohort and nested case-control designs will be generalized to deal with more complex multi-state disease processes. Efficient Design of Tracing Studies for Cohorts with Attrition I will develop frameworks for the efficient design of tracing studies geared toward the collection of auxiliary data on the disease and withdrawal process in cohort studies. These data facilitate correction for biases arising from data which are MNAR and enhance efficiency. Frameworks for analysis include illness-death models where interest lies in the development of co-morbidities or disease complications, progressive models for degenerative conditions, and survival models. Use of auxiliary covariate data and inverse probability weights will ensure valid inference. If individuals do not consent to be traced then additional weights for non-response will be incorporated. Moreover traced individuals may only provide partial or surrogate responses, in which case methods accommodating incomplete or mismeasured responses will warrant development. Design and Analysis of Family Studies with Auxiliary Data Genetic, phenotype (e.g. age of onset) and auxiliary data can be exploited to develop efficient selection models for choosing probands from disease registries for inclusion in family studies. I will develop sample selection models which incorporate such information, as well as possible surrogate summary proband-reported data on family members. The biased sample scheme employed in family studies means there is little information on disease onset times. I will explore the utility of auxiliary data in the development of score tests of genetic associations. While work has been carried out on the analysis of family data for binary and time-to-event outcomes, little has been done for modeling within-family dependencies in more complex multistage disease processes; I will focus on this.

动态过程的响应相关两阶段设计 我将开发创新的方法，选择个体进行大型队列中的生物标志物子研究，旨在检查遗传和血清生物标志物与纵向反应之间的关系，这可能涉及重复测量和事件发生时间数据。第一阶段样本涉及收集纵向或生活史数据沿着与生物库中储存的标本。 第二阶段样本是由一组个体定义的，这些个体的储存标本被测定，然后可以用于分析。将根据大样本理论开发II期样本的最佳选择算法，根据纵向分析的框架（即边际分析、分层混合效应模型、过渡模型）获得不同的选择模型。 还将使用似然和加权估计函数开发病例队列设计数据的二次分析方法，以校正偏倚样本。 将推广病例队列和嵌套病例对照设计，以处理更复杂的多状态疾病过程。 阿托伐他汀队列追踪研究的有效设计 我将为追踪研究的有效设计开发框架，以收集队列研究中疾病和退出过程的辅助数据。 这些数据有助于纠正MNAR数据产生的偏差，并提高效率。 分析框架包括疾病-死亡模型，其中关注的是合并症或疾病并发症的发展，退行性疾病的进展模型和生存模型。使用辅助协变量数据和逆概率权重将确保有效的推断。如果个人不同意被追踪，则将纳入不回答的额外权重。此外，被追踪的个人可能只提供部分或替代反应，在这种情况下，需要开发适应不完整或错误测量反应的方法。 辅助资料家系研究的设计与分析 可以利用遗传、表型（例如发病年龄）和辅助数据来开发有效的选择模型，用于从疾病登记处选择先证者，以纳入家族研究。我将开发样本选择模型，其中包括这些信息，以及可能的替代总结先证者报告的家庭成员的数据。 在家庭研究中采用的有偏抽样方案意味着关于疾病发作时间的信息很少。我将探讨辅助数据的效用在发展的得分测试的遗传协会。 虽然工作已经进行了家庭数据的二进制和时间到事件的结果分析，几乎没有做过更复杂的多阶段疾病过程中的家庭内的依赖关系建模，我将集中在这一点。