Statistical Methods for Multilevel Multivariate Functional Studies

说明(申请人提供)：迫切需要采用标准的统计方法，并开发新的方法来分析非常大的数据集。如果数据集引起了非常困难或无法克服的计算问题，那么它就是非常大的 用于使用现有计算系统进行标准数据分析。数据集的大小和复杂性的加速增长在一定程度上是由于计算和存储能力的提高、新的测量技术、研究设计以及研究“单元”的数量不断增加。这项提议涉及用于分析新兴类型的超大数据集的统计方法，在这些数据集中，图像或密集采样的生物信号等非常高维的结果和预测值被记录在对成百上千个对象的多次访问中。所提出的方法将描述在纵向研究中的横截面、纵向和测量误差变异性，其中观察数据是函数或图像。对于高维预报器的情况，还将讨论标量函数/图像回归分析的方法。所提出的方法受到睡眠和扩散张量成像(DTI)脑束成像(DTI)的大规模研究的启发并应用于此。 公共卫生相关性：该项目为非常大的数据集提供统计分析方法，在这些数据集中，在多次访问时测量图像或密集采样的生物信号。方法应用于多发性硬化(MS)和健康受试者的扩散张量成像(DTI)获得的纵向睡眠脑电(EEG)数据和脑电地形图。

DESCRIPTION (provided by applicant): There is an acute and increasing need to adapt standard statistical methods and to develop new approaches for the analysis of very large data sets. A data set is very large if it raises very difficult or insurmountable computational problems for standard data analysis using available computing systems. The accelerated increase in size and complexity of data sets is due in part to increased computational and storage capabilities, new measurement technologies, study designs, and an increasing number of study "units." This proposal is concerned with statistical methods for the analysis of an emerging type of very large data set, where very high dimensional outcomes and predictors, such as images or densely sampled biosignals, are recorded at multiple visits on hundreds or thousands of subjects. The methods proposed will describe the cross-sectional, longitudinal and measurement error variability in longitudinal studies where observed data are functions or images. Methods for scalar on function/image regression analysis will also be addressed for the case of very highly dimensional predictors. The proposed methodology is inspired by and applied to very large studies of sleep and Diffusion Tensor Imaging (DTI) brain tractography. PUBLIC HEALTH RELEVANCE: The project provides statistical analysis methods for very large data sets where images or densely sampled biological signals are measured at multiple visits. Methods are applied to longitudinal sleep electroencephalogram (EEG) data and brain tractography obtained from Diffusion Tensor Imaging (DTI) in Multiple Sclerosis (MS) and healthy subjects.