Bootstrap-based inference on the difference in the means of two correlated functional processes

Ciprian M. Crainiceanu, Ana Maria Staicu, Shubankar Ray, Naresh Punjabi

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)3223-3240
Number of pages18
JournalStatistics in Medicine
Issue number26
StatePublished - Nov 20 2012


  • EEG
  • Measurement error
  • Penalized splines
  • Sleep
  • Spectrogram

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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