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Modeling sleep fragmentation in sleep hypnograms: An instance of fast, scalable discrete-state, discrete-time analyses

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  • Swihart, Bruce J.
  • Punjabi, Naresh M.
  • Crainiceanu, Ciprian M.

Abstract

Methods are introduced for the analysis of large sets of sleep study data (hypnograms) using a 5-state 20-transition-type structure defined by the American Academy of Sleep Medicine. Application of these methods to the hypnograms of 5598 subjects from the Sleep Heart Health Study provide: the first analysis of sleep hypnogram data of such size and complexity in a community cohort with a range of sleep-disordered breathing severity; introduce a novel approach to compare 5-state (20-transition-type) to 3-state (6-transition-type) sleep structures to assess information loss from combining sleep state categories; extend current approaches of multivariate survival data analysis to clustered, recurrent event discrete-state discrete-time processes; and provide scalable solutions for data analyses required by the case study. The analysis provides detailed new insights into the association between sleep-disordered breathing and sleep architecture. The example data and both R and SAS code are included in online supplementary materials.

Suggested Citation

  • Swihart, Bruce J. & Punjabi, Naresh M. & Crainiceanu, Ciprian M., 2015. "Modeling sleep fragmentation in sleep hypnograms: An instance of fast, scalable discrete-state, discrete-time analyses," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 1-11.
    • Handle: RePEc:eee:csdana:v:89:y:2015:i:c:p:1-11
    DOI: 10.1016/j.csda.2015.03.001
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    References listed on IDEAS

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    1. Crainiceanu, Ciprian M. & Caffo, Brian S. & Di, Chong-Zhi & Punjabi, Naresh M., 2009. "Nonparametric Signal Extraction and Measurement Error in the Analysis of Electroencephalographic Activity During Sleep," Journal of the American Statistical Association, American Statistical Association, vol. 104(486), pages 541-555.
    2. Odd O. Aalen & Johan Fosen & Harald Weedon-Fekjær & Ørnulf Borgan & Einar Husebye, 2004. "Dynamic Analysis of Multivariate Failure Time Data," Biometrics, The International Biometric Society, vol. 60(3), pages 764-773, September.
    3. Bingqing Zhou & Aurelien Latouche & Vanderson Rocha & Jason Fine, 2011. "Competing Risks Regression for Stratified Data," Biometrics, The International Biometric Society, vol. 67(2), pages 661-670, June.
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