| 书目名称 | Statistical Methods for Environmental Epidemiology with R |
| 副标题 | A Case Study in Air |
| 编辑 | Francesca Dominici,Roger D. Peng |
| 视频video | |
| 概述 | 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 purpo |
| 丛书名称 | Use R! |
| 图书封面 |  |
| 描述 | 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 m |
| 出版日期 | Book 2008 |
| 关键词 | NMMAPS; Radiologieinformationssystem; air pollution; reproducible research; semiparametric models; time s |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-0-387-78167-9 |
| isbn_softcover | 978-0-387-78166-2 |
| isbn_ebook | 978-0-387-78167-9Series ISSN 2197-5736 Series E-ISSN 2197-5744 |
| issn_series | 2197-5736 |
| copyright | Springer-Verlag New York 2008 |
发表于 2025-3-21 18:00:24
