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Unpublished Paper
BOOTSTRAP-BASED INFERENCE ON THE DIFFERENCE IN THE MEANS OF TWO CORRELATED FUNCTIONAL PROCESSES
Johns Hopkins University, Dept. of Biostatistics Working Papers
  • Ciprian M. Crainiceanu, Bloomberg School of Public Health, Department of Biostatistics, Johns Hopkins
  • Ana-Maria Staicu, North Carolina State University, Department of Statistics
  • Shubankar Ray, Merck & Company, Biometrics Research
  • Naresh Punjabi, Johns Hopkins Bloomberg School of Public Health, Department of Epidemiology
Date of this Version
3-7-2012
Abstract

Nonparametric inference methods on the mean difference between two correlated Functional processes are proposed. 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 hours after sleep onset. Data are obtained from the Sleep Heart Health Study (SHHS), the largest community cohort study of sleep. While methods are applied to a single case study, they can be applied to a large number of studies that have correlated functional data.

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Citation Information
Ciprian M. Crainiceanu, Ana-Maria Staicu, Shubankar Ray and Naresh Punjabi. "BOOTSTRAP-BASED INFERENCE ON THE DIFFERENCE IN THE MEANS OF TWO CORRELATED FUNCTIONAL PROCESSES" (2012)
Available at: http://works.bepress.com/ciprian_crainiceanu/24/