title: Bootstrap-based inference on the difference in the means of two correlated functional processes.
abstract: We propose nonparametric inference methods on the mean difference between two correlated functional processes. We compare methods that (1) incorporate different levels of smoothing of the mean and covariance; (2) preserve the sampling design; and (3) use parametric and nonparametric estimation of the mean functions. We apply our method to estimating the mean difference between average normalized δ power of sleep electroencephalograms for 51 subjects with severe sleep apnea and 51 matched controls in the first 4  h after sleep onset. We obtain data from the Sleep Heart Health Study, the largest community cohort study of sleep. Although methods are applied to a single case study, they can be applied to a large number of studies that have correlated functional data.
authors.affiliation: Department of Biostatistics, Johns Hopkins University, 615 N. Wolfe St., Baltimore, MD 21205, U.S.A. ccrainic@jhsph.edu
authors.forename: Ciprian M
authors.initials: CM
authors.lastname: Crainiceanu
authors.forename: Ana-Maria
authors.initials: AM
authors.lastname: Staicu
authors.forename: Shubankar
authors.initials: S
authors.lastname: Ray
authors.forename: Naresh
authors.initials: N
authors.lastname: Punjabi
mesh_terms: D056808:Biostatistics / Q000379:methods*; D015331:Cohort Studies; D016001:Confidence Intervals; D006801:Humans; D015233:Models, Statistical; D012891:Sleep Apnea Syndromes / Q000175:diagnosis / Q000209:etiology; D018709:Statistics, Nonparametric