000 04551nam a22004455i 4500
001 978-0-387-78167-9
003 DE-He213
005 20161121231210.0
007 cr nn 008mamaa
008 100301s2008 xxu| s |||| 0|eng d
020 _a9780387781679
_9978-0-387-78167-9
024 7 _a10.1007/978-0-387-78167-9
_2doi
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMBNS
_2bicssc
072 7 _aMED090000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aDominici, Francesca.
_eauthor.
245 1 0 _aStatistical Methods for Environmental Epidemiology with R
_h[electronic resource] :
_bA Case Study in Air Pollution and Health /
_cby Francesca Dominici, Roger D. Peng.
264 1 _aNew York, NY :
_bSpringer New York,
_c2008.
300 _aX, 144 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aUse R
505 0 _aStudies of Air Pollution and Health -- 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 Particulate Matter and Mortality in the United States.
520 _aAdvances 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.
650 0 _aStatistics.
650 1 4 _aStatistics.
650 2 4 _aStatistics for Life Sciences, Medicine, Health Sciences.
700 1 _aPeng, Roger D.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387781662
830 0 _aUse R
856 4 0 _uhttp://dx.doi.org/10.1007/978-0-387-78167-9
912 _aZDB-2-SMA
950 _aMathematics and Statistics (Springer-11649)
999 _c510004
_d510004