Statistical Methods For Longitudinal And Other Studies

纵向研究和其他研究的统计方法

• 批准号: 6541926
• 负责人: Kai F Yu
• 金额: --
• 依托单位: EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/6541926
• 关键词: clinical research; computer data analysis; data collection methodology /evaluation; disease /disorder proneness /risk; epidemiology; human data; longitudinal human study; perinatal; statistics /biometry

This project will investigate theory, methods and applications of mathematical statistics and probability, with particular emphasis on the problems with data collected by NICHD. Current focus is on 1) the analysis of data arising from longitudinal studies with repeated measurements, 2) the adjustment of odds ratio with missing values in epidemiological studies, and 3) the testing for disease clustering in communities. Examples of NICHD projects on longitudinal studies are Successive Small-for-Gestational Age Study I and Study II in Alabama and Scandinavia, Preventing Problem Behavior Among Middle School Students and the Longitudinal Study of Vaginal Flora. A host of statistical procedures for estimation and hypothesis testing will be proposed and investigated for the time varying coefficient models via their asymptotic properties and simulations. Applications will be developed to handle questions concerning various issues in perinatal and reproductive epidemiology. Data will be fitted to growth models such as Rossavik model, linear model and logistic model. New and rigorous statistical methods and algorithms will be generated and validated through investigation of their statistical and probabilistic properties. Computer-intensive techniques such as bootstrapping methodology will be investigated for the relevant problems. Among the applications of the developed methodology are fetal growth, maternal risk factors and pregnancy outcomes.

该项目将研究数学统计和概率的理论，方法和应用，并特别强调NICHD收集的数据问题。当前的重点是1）通过重复测量的纵向研究产生的数据分析，2）在流行病学研究中的优势比的调整和缺失值的调整，以及3）社区中疾病聚类的测试。纵向研究的NICHD项目的例子是在阿拉巴马州和斯堪的纳维亚半岛的连续小胎龄研究I和研究II，从而阻止了中学生的问题行为以及阴道菌群的纵向研究。将通过其渐近性能和模拟来提出大量用于估计和假设检验的统计程序。将开发应用程序来处理有关围产期和生殖流行病学各种问题的问题。数据将适用于Rossavik模型，线性模型和Logistic模型等增长模型。通过研究其统计和概率特性，将生成和验证新的和严格的统计方法和算法。将针对相关问题研究计算机密集型技术，例如引导方法。在开发方法的应用中，有胎儿的生长，母体危险因素和妊娠结局。