Statistical Methods for Environmental Epidemiology with R (eBook)

A Case Study in Air Pollution and Health

Roger D. Peng, Francesca Dominici (Autoren)

eBook Download: PDF

2008 | 2008
X, 144 Seiten
Springer New York (Verlag)
978-0-387-78167-9 (ISBN)

Infos

As an area of statistical application, environmental epidemiology and more speci cally, the estimation of health risk associated with the exposure to - vironmental agents, has led to the development of several statistical methods and software that can then be applied to other scienti c areas. The stat- tical analyses aimed at addressing questions in environmental epidemiology have the following characteristics. Often the signal-to-noise ratio in the data is low and the targets of inference are inherently small risks. These constraints typically lead to the development and use of more sophisticated (and pot- tially less transparent) statistical models and the integration of large hi- dimensional databases. New technologies and the widespread availability of powerful computing are also adding to the complexities of scienti c inves- gation by allowing researchers to t large numbers of models and search over many sets of variables. As the number of variables measured increases, so do the degrees of freedom for in uencing the association between a risk factor and an outcome of interest. We have written this book, in part, to describe our experiences developing and applying statistical methods for the estimation for air pollution health e ects. Our experience has convinced us that the application of modern s- tistical methodology in a reproducible manner can bring to bear subst- tial bene ts to policy-makers and scientists in this area. We believe that the methods described in this book are applicable to other areas of environmental epidemiology, particularly those areas involving spatial{temporal exposures.

Inhalt

Studies of air pollution and health. - Introduction to R and air pollution and health data. - Reproducible research tools. - Statistical issues in estimating the health effects of spatial-temporal environmental exposures. - Exploratory data analyses. - Statistical models. - Pooling risks across locations and quantifying spatial heterogeneity. -A reproducible seasonal analysis of PM10 and mortaility in the U.S.

Produkt-Details

• Erscheint lt. Verlag: 15.12.2008
• Reihe/Serie: Use R!
• Reihe/Serie: Use R!
• Zusatzinfo: X, 144 p.
• Verlagsort: New York
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Medizin / Pharmazie ► Allgemeines / Lexika
• Themenwelt: Naturwissenschaften ► Biologie ► Ökologie / Naturschutz
• Themenwelt: Technik
• Schlagworte: Air Pollution • NMMAPS • Radiologieinformationssystem • reproducible research • Semiparametric Models • Time Series
• ISBN-10: 0-387-78167-6 / 0387781676
• ISBN-13: 978-0-387-78167-9 / 9780387781679