Multilevel functional principal component analysis

摘要: The Sleep Heart Health Study (SHHS) is a comprehensive landmark study of sleep and its impacts on health outcomes. A primary metric the SHHS in-home polysomnogram, which includes two electroencephalographic (EEG) channels for each subject, at visits. volume importance this data presents enormous challenges analysis. To address these challenges, we introduce multilevel functional principal component analysis (MFPCA), novel statistical methodology designed to extract core intra- inter-subject geometric components data. Though motivated by SHHS, proposed generally applicable, with potential relevance many modern scientific studies hierarchical or longitudinal Notably, using MFPCA, identify quantify associations between EEG activity during adverse cardiovascular