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Food and Drug Administration, Washington, DC, USA ***
Only three decades ago, the interpretation, and even a statistical analysis,
of biological data on time-varying functions was nearly always performed
without regard for any time structure. Purely static interpretations of mea-
surements, sometimes based on a single 'snapshot' and interpreted without
any temporal reference, seemed to suffice for diagnostic and other aims in
biomedicine. Even today, many physicians rely on blood pressure measure.
ments at very few arbitrary time-points, although it has long been known
that the values vary greatly along several time scales in health, Fig. 1, and
disease, Fig. 219, 20
What can be said for human blood pressure also applies to core temper.
ature. Although an about 24-h temperature rhythm has long been known,
there does not seem to be much motivation for the routine application of
methods of regression and time series analysis to biological temperature se-
ries, as is practiced in many other sciences such as physics, engineering and
economics. By the same token, the relationships of structural components
among several biological variables are usually regarded from a static point
of view, as more or less immutable features, for a given person and set of
Key-words: Acrophase-test; Amplitude-test; Chronobiologic serial section; Chronobiologic window; Chrono-
desm; Frequency; Mesor-test; Ortophase; Parameter test; Period; Population-mean cosinor; Short series; Sin-
gle cosinor.
Support: National Institute of General Medical Sciences (GM-13981), National Cancer Institute
(CA-14445), National Institute of Aging (AG-00158), National Institute of Occupational Safety
and Health (OH-00631).
Presented at workshop on methods held after the XVth Meeting of the International Society
for Chronobiology held in September 1981 in Minneapolis, Minnesota, USA.
Received June 7, 1982.
Chronobiologia 9, 397, 1982,
397