title: Population Value Decomposition, a Framework for the Analysis of Image Populations.
abstract: Images, often stored in multidimensional arrays, are fast becoming ubiquitous in medical and public health research. Analyzing populations of images is a statistical problem that raises a host of daunting challenges. The most significant challenge is the massive size of the datasets incorporating images recorded for hundreds or thousands of subjects at multiple visits. We introduce the population value decomposition (PVD), a general method for simultaneous dimensionality reduction of large populations of massive images. We show how PVD can be seamlessly incorporated into statistical modeling, leading to a new, transparent, and rapid inferential framework. Our PVD methodology was motivated by and applied to the Sleep Heart Health Study, the largest community-based cohort study of sleep containing more than 85 billion observations on thousands of subjects at two visits. This article has supplementary material online.
authors.affiliation: Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St., Baltimore, MD 21205.
authors.forename: Ciprian M
authors.initials: CM
authors.lastname: Crainiceanu
authors.affiliation: Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St., Baltimore, MD 21205.
authors.forename: Brian S
authors.initials: BS
authors.lastname: Caffo
authors.affiliation: Division of Biostatistics, School of Public Health, University of Texas Health Science Center at Houston, 1200 Herman Pressler Dr, Houston, TX 77030.
authors.forename: Sheng
authors.initials: S
authors.lastname: Luo
authors.affiliation: Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St., Baltimore, MD 21205.
authors.forename: Vadim M
authors.initials: VM
authors.lastname: Zipunnikov
authors.affiliation: Department of Epidemiology, Johns Hopkins University, 615 N. Wolfe St., Baltimore, MD 21205.
authors.forename: Naresh M
authors.initials: NM
authors.lastname: Punjabi
keywords: Electroencephalography; Signal extraction