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The Statistical Analysis of Circadian Phase and Amplitude in Constant-Routine Core-Temperature Data
Emery N. Brown
Laboratory for Circadian and Sleep Disorders Medicine, Endocrine Division, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts 02115, Department of Anesthesia, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts 02114
Charles A. Czeisler
Laboratory for Circadian and Sleep Disorders Medicine, Endocrine Division, Department of Medicine, Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts 02115
Accurate estimation of the phases and amplitude of the endogenous circadian pacemaker from constant-routine core-temperature series is crucial for making inferences about the properties of the human biological clock from data collected under this protocol. This paper presents a set of statistical methods based on a harmonic-regression-plus-correlated-noise model for estimating the phases and the amplitude of the endogenous circadian pacemaker from constant-routine core-temperature data. The methods include a Bayesian Monte Carlo procedure for computing the uncertainty in these circadian functions. We illustrate the techniques with a detailed study of a single subject's core-temperature series and describe their relationship to other statistical methods for circadian data analysis. In our laboratory, these methods have been successfully used to analyze more than 300 constant routines and provide a highly reliable means of extracting phase and amplitude information from core-temperature data.
Key Words: Bayesian analysis • circadian rhythms • correlated noise • harmonic regression • internal time • Kalman filter • maximum-likelihood estimation • Monte Carlo methods
Journal of Biological Rhythms, Vol. 7, No. 3,
177-202 (1992)
DOI: 10.1177/074873049200700301
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