Seasonal patterns have been found in a remarkable range of
health conditions, including birth defects, respiratory infections
and cardiovascular disease. Accurately estimating the size and
timing of seasonal peaks in disease incidence is an aid to
understanding the causes and possibly to developing interventions.
With global warming increasing the intensity of seasonal weather
patterns around the world, a review of the methods for estimating
seasonal effects on health is timely.
This is the first book on statistical methods for seasonal data
written for a health audience. It describes methods for a range of
outcomes (including continuous, count and binomial data) and
demonstrates appropriate techniques for summarising and modelling
these data. It has a practical focus and uses interesting examples
to motivate and illustrate the methods. The statistical procedures
and example data sets are available in an R package called season
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