Non-Fiction Books:

Analysing Seasonal Health Data

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Analysing Seasonal Health Data by Adrian Barnett
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Description

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'.

Author Biography

Adrian Barnett is a senior research fellow at Queensland University of Technology, Australia. Annette Dobson is a Professor of Biostatistics at The University of Queensland, Australia. Both are experienced medical statisticians with a commitment to statistical education and have previously collaborated in research in the methodological developments and applications of biostatistics, especially to time series data. Among other projects, they worked together on revising the well-known textbook "An Introduction to Generalized Linear Models," third edition, Chapman Hall/CRC, 2008. In their new book they share their knowledge of statistical methods for examining seasonal patterns in health.
Release date Australia
February 12th, 2010
Country of Publication
Germany
Edition
2010 ed.
Illustrations
112 Illustrations, black and white; XIII, 164 p. 112 illus.
Imprint
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Pages
164
Dimensions
156x234x11
ISBN-13
9783642107474
Product ID
3952252

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