Empirical likelihood-based inference for functional means with application to wearable device data

• 成果类型: Article
• 署名作者: Chang, Hsin-wen; McKeague, Ian W.
• 署名单位: Academia Sinica - Taiwan; Columbia University
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/rssb.12543
• 发表日期: 2022
• 页码: 1947-1968
• 关键词: one-way anova; physical-activity; survival functions; tests; SPARSE; bands

摘要

This paper develops a nonparametric inference framework that is applicable to occupation time curves derived from wearable device data. These curves consider all activity levels within the range of device readings, which is preferable to the practice of classifying activity into discrete categories. Motivated by certain features of these curves, we introduce a powerful likelihood ratio approach to construct confidence bands and compare functional means. Notably, our approach allows discontinuities in the functional covariances while accommodating discretization of the observed trajectories. A simulation study shows that the proposed procedures outperform competing functional data procedures. We illustrate the proposed methods using wearable device data from an NHANES study.