Description |
1 online resource (xv, 432 pages) : illustrations, maps |
Physical Medium |
polychrome |
Description |
text file |
Summary |
Environmental epidemiology is the study of the environmental causes of disease in populations and how these risks vary in relation to intensity and duration of exposure and other factors like genetic susceptibility. As such, it is the basic science upon which governmental safety standards and compensation policies for environmental and occupational exposure are based. Profusely illustrated with examples from the epidemiologic literature on ionizing radiation and air pollution, thistext provides a systematic treatment of the statistical challenges that arise in environmental health studies and. |
Bibliography |
Includes bibliographical references (pages 368-425) and index. |
Contents |
A tale of two exposures -- Basic epidemiologic study designs -- Basic statistical methods -- Multivariate models -- Some special-purpose designs -- Modeling exposure-time-response relationships -- Longitudinal models -- Time-series models for acute effects -- Spatial models -- Ecologic inference -- Measurement error and exposure models -- Multiple risk factors and interactions -- Mechanistic models -- Intervention studies -- Risk assessment -- Probability of causation and compensation -- Further challenges. |
Local Note |
eBooks on EBSCOhost EBSCO eBook Subscription Academic Collection - North America |
Subject |
Environmentally induced diseases -- Epidemiology -- Statistical methods.
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Environmentally induced diseases -- Epidemiology. |
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Statistics. |
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Environmentally induced diseases. |
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Environmental Monitoring. |
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Epidemiologic Methods. |
Genre/Form |
Electronic books.
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Other Form: |
Print version: Thomas, Duncan C. Statistical methods in environmental epidemiology. Oxford ; New York : Oxford University Press, 2009 9780199232895 |
ISBN |
9780191552687 (electronic book) |
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0191552682 (electronic book) |
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9780199232895 (hardback) |
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019923289X (hardback) |
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9780199232901 (paperback) |
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0199232903 (paperback) |
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