289 citations · 554 across the 25 of their papers we have counts for
13 papers · 1 filter
Sensitivity analysis for matching on high-dimensional predictors: A case study of racial disparity in US mortality
Marina Hernandez, Ciprian Crainiceanu
Matching on a low dimensional vector of scalar covariates consists of constructing groups of individuals in which each individual in a group is within a pre-specified distance from…
Walking fingerprinting
Lily Koffman, Ciprian Crainiceanu, Andrew Leroux
We consider the problem of predicting an individual's identity from accelerometry data collected during walking. In a previous paper we introduced an approach that transforms the a…
Epidemiology of Objectively Measured Bedtime and Chronotype in the US adolescents and adults: NHANES 2003-2006
Jacek K. Urbanek, Adam Spira, Junrui Di +3
Background: We propose a method for estimating the timing of in-bed intervals using objective data in a large representative U.S. sample, and quantify the association between these…
Relating multi-sequence longitudinal intensity profiles and clinical covariates in new multiple sclerosis lesions
Elizabeth M. Sweeney, Russell T. Shinohara, Blake E. Dewey +5
Structural magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients. The formation of these lesions is a complex process inv…
Prediction of sustained harmonic walking in the free-living environment using raw accelerometry data
Jacek K. Urbanek, Vadim Zipunnikov, Tamara Harris +6
Objective. Using raw, sub-second level, accelerometry data, we propose and validate a method for identifying and characterizing walking in the free-living environment. We focus on…
Longitudinal high-dimensional principal components analysis with application to diffusion tensor imaging of multiple sclerosis
Vadim Zipunnikov, Sonja Greven, Haochang Shou +3
We develop a flexible framework for modeling high-dimensional imaging data observed longitudinally. The approach decomposes the observed variability of repeatedly measured high-dim…
Movement Prediction Using Accelerometers in a Human Population
Luo Xiao, Bing He, Annemarie Koster +5
We introduce statistical methods for predicting the types of human activity at sub-second resolution using triaxial accelerometry data. The major innovation is that we use labeled…
Soft Null Hypotheses: A Case Study of Image Enhancement Detection in Brain Lesions
Haochang Shou, Russell T. Shinohara, Han Liu +2
This work is motivated by a study of a population of multiple sclerosis (MS) patients using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to identify active brain…
Structured Functional Principal Component Analysis
Haochang Shou, Vadim Zipunnikov, Ciprian M. Crainiceanu +1
Motivated by modern observational studies, we introduce a class of functional models that expands nested and crossed designs. These models account for the natural inheritance of co…
Parametrization of white matter manifold-like structures using principal surfaces
Chen Yue, Vadim Zipunnikov, Pierre-Louis Bazin +4
In this manuscript, we are concerned with data generated from a diffusion tensor imaging (DTI) experiment. The goal is to parameterize manifold-like white matter tracts, such as th…
Homotopic Group ICA for Multi-Subject Brain Imaging Data
Juemin Yang, Ani Eloyan, Anita Barber +5
Independent Component Analysis (ICA) is a computational technique for revealing latent factors that underlie sets of measurements or signals. It has become a standard technique in…
Nonlinear tube-fitting for the analysis of anatomical and functional structures
Jeff Goldsmith, Brian Caffo, Ciprian Crainiceanu +3
We are concerned with the estimation of the exterior surface and interior summaries of tube-shaped anatomical structures. This interest is motivated by two distinct scientific goal…
Multilevel functional principal component analysis
Chong-Zhi Di, Ciprian M. Crainiceanu, Brian S. Caffo +1
The Sleep Heart Health Study (SHHS) is a comprehensive landmark study of sleep and its impacts on health outcomes. A primary metric of the SHHS is the in-home polysomnogram, which…