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| Content Provider | PubMed Central |
|---|---|
| Author | Zigler, Corwin M. Dominici, Francesca Wang, Yun |
| Copyright Year | 2012 |
| Abstract | Methods for causal inference regarding health effects of air quality regulations are met with unique challenges because (1) changes in air quality are intermediates on the causal pathway between regulation and health, (2) regulations typically affect multiple pollutants on the causal pathway towards health, and (3) regulating a given location can affect pollution at other locations, that is, there is interference between observations. We propose a principal stratification method designed to examine causal effects of a regulation on health that are and are not associated with causal effects of the regulation on air quality. A novel feature of our approach is the accommodation of a continuously scaled multivariate intermediate response vector representing multiple pollutants. Furthermore, we use a spatial hierarchical model for potential pollution concentrations and ultimately use estimates from this model to assess validity of assumptions regarding interference. We apply our method to estimate causal effects of the 1990 Clean Air Act Amendments among approximately 7 million Medicare enrollees living within 6 miles of a pollution monitor. |
| Related Links | http://dx.doi.org/10.1093/biostatistics/kxr052 |
| Ending Page | 302 |
| Page Count | 14 |
| Starting Page | 289 |
| File Format | |
| ISSN | 14654644 |
| e-ISSN | 14684357 |
| Journal | Biostatistics (Oxford, England) |
| Issue Number | 2 |
| Volume Number | 13 |
| Language | English |
| Publisher | Oxford University Press |
| Publisher Date | 2012-04-01 |
| Access Restriction | Open |
| Rights Holder | Oxford University Press |
| Subject Keyword | Statistics, Probability and Uncertainty Statistics and Probability Medicine(all) Research in Higher Education |
| Content Type | Text |
| Resource Type | Article |
| Subject | Statistics and Probability Medicine Statistics, Probability and Uncertainty |
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