Abstract #300498

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JSM 2003 Abstract #300498
Activity Number: 472
Type: Contributed
Date/Time: Thursday, August 7, 2003 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #300498
Title: Stochastic Modeling of Sleep Duration Data
Author(s): Marilisa Gibellato*+ and Haikady N. Nagaraja
Companies: The Ohio State University and Ohio State University
Address: 2523 Dahlia Way, Columbus, OH, 43235,
Keywords: sleep ; goodness of fit ; generalized gamma ; Weibull
Abstract:

During aging, individuals experience decreasing total sleep time and ability to remain asleep. Modeling the successive sleep duration times in each group may yield measures that can reflect the status of these changes. Sleep duration times (defined as the lengths of time spent between awakenings) were collected from 29 healthy normal sleepers either young (20-35) or older (70-79) monitored during seven calendar days in temporal isolation. A maximum likelihood procedure was used to fit the generalized gamma distribution (GENG) to each subject's sleep duration times. Kolmogorov-Smirnov goodness-of-fit tests determined that all but one dataset could be reasonably modeled using a GENG which includes the exponential and Weibull as special cases. Independence was verified between the observations by transformation to standard normal scores and autocorrelation function plots. Disparity in parameter estimates between the groups may reflect the observation that sleep becomes more "fragile" with age.

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