EcoSta 2018: Registration
View Submission - EcoSta2018
A0659
Title: Nonparametric comparisons of activity level data from wearable devices Authors:  Hsin-wen Chang - Academia Sinica (Taiwan) [presenting]
Ian McKeague - Columbia University (United States)
Abstract: The motivation comes from applications to health care monitoring in which there is a need to compare groups of subjects in terms of health outcomes that are functional in nature. We develop nonparametric methods to compare distributions between groups of subjects based on functional data collected from wearable devices. A simulation study shows that the new procedures can deal with unmeasured time-dependent confounders. We illustrate the proposed methods using data from the Darmouth Student Life study.