Logo - springer
Slogan - springer

Statistics - Life Sciences, Medicine & Health | Statistical Methods for Environmental Epidemiology with R - A Case Study in Air Pollution and

Statistical Methods for Environmental Epidemiology with R

A Case Study in Air Pollution and Health

Series: Use R!

Peng, Roger D., Dominici, Francesca

2008, X, 144p.

Available Formats:
eBook
Information

Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.

You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.

After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.

 
$59.95

(net) price for USA

ISBN 978-0-387-78167-9

digitally watermarked, no DRM

Included Format: PDF

download immediately after purchase


learn more about Springer eBooks

add to marked items

Softcover
Information

Softcover (also known as softback) version.

You can pay for Springer Books with Visa, Mastercard, American Express or Paypal.

Standard shipping is free of charge for individual customers.

 
$79.95

(net) price for USA

ISBN 978-0-387-78166-2

free shipping for individuals worldwide

usually dispatched within 3 to 5 business days


add to marked items

  • Summarizes current methodology for conducting time series analysis in environmental epidemiology
  • R packages are available under a free software license for readers to use and adapt for their own purposes
  • Complete national datasets on air pollution and mortality available for reproducing and extending the analyses in the book

Advances in statistical methodology and computing have played an important role in allowing researchers to more accurately assess the health effects of ambient air pollution. The methods and software developed in this area are applicable to a wide array of problems in environmental epidemiology. This book provides an overview of the methods used for investigating the health effects of air pollution and gives examples and case studies in R which demonstrate the application of those methods to real data. The book will be useful to statisticians, epidemiologists, and graduate students working in the area of air pollution and health and others analyzing similar data.

The authors describe the different existing approaches to statistical modeling and cover basic aspects of analyzing and understanding air pollution and health data. The case studies in each chapter demonstrate how to use R to apply and interpret different statistical models and to explore the effects of potential confounding factors. A working knowledge of R and regression modeling is assumed. In-depth knowledge of R programming is not required to understand and run the examples.

Researchers in this area will find the book useful as a ``live'' reference. Software for all of the analyses in the book is downloadable from the web and is available under a Free Software license. The reader is free to run the examples in the book and modify the code to suit their needs. In addition to providing the software for developing the statistical models, the authors provide the entire database from the National Morbidity Mortality and Air Pollution Study (NMMAPS) in a convenient R package. With the database, readers can run the examples and experiment with their own methods and ideas.

Roger D. Peng is an Assistant Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. He is a prominent researcher in the areas of air pollution and health risk assessment and statistical methods for spatial and temporal data. Dr. Peng is the author of numerous R packages and is a frequent contributor to the R mailing lists.

Francesca Dominici is a Professor in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. She has published extensively on hierarchical and semiparametric modeling and has been the leader of major national studies of the health effects of air pollution. She has also participated in numerous panels conducted by the National Academy of Science assessing the health effects of environmental exposures and has consulted for the US Environmental Protection Agency's Clean Air Act Advisory Board.

Content Level » Research

Keywords » NMMAPS - Radiologieinformationssystem - air pollution - reproducible research - semiparametric models - time series

Related subjects » Life Sciences, Medicine & Health

Table of contents / Preface / Sample pages 

Popular Content within this publication 

 

Articles

Read this Book on Springerlink

Services for this book

New Book Alert

Get alerted on new Springer publications in the subject area of Statistics for Life Sciences, Medicine, Health Sciences.