Investigation of excess environmental risk around putative sources: Stone's test with covariate adjustment
| Autor: | Tony Morton-Jones, Paul Elliott, Peter J. Diggle |
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| Rok vydání: | 1999 |
| Předmět: |
Statistics and Probability
Epidemiology Incineration Poisson distribution Lambda Models Biological Statistics Nonparametric symbols.namesake Risk Factors Stomach Neoplasms Statistics Linear regression Covariate Humans Computer Simulation Poisson Distribution Statistical hypothesis testing Mathematics Air Pollutants Estimation theory Carcinogens Environmental Regression symbols Regression Analysis Null hypothesis Monte Carlo Method Algorithms |
| Zdroj: | Statistics in Medicine. 18:189-197 |
| ISSN: | 1097-0258 0277-6715 |
| DOI: | 10.1002/(sici)1097-0258(19990130)18:2<189::aid-sim7>3.0.co;2-y |
| Popis: | Stone (Statistics in Medicine, 7, 649-660 (1988)) proposed a method of testing for elevation of disease risk around a point source. Stone's test is appropriate to data consisting of counts of the numbers of cases, Yi say, in each of n regions which can be ordered in increasing distance from a point source. The test assumes that the Yi are mutually independent Poisson variates, with means mu i = Ei lambda i where the Ei are the expected numbers of cases, for example based on appropriately standardized national incidence rates, and the lambda i are relative risks. The null hypothesis that the lambda i are constant is then tested against the alternative that they are monotone non-increasing with distance from the source. We propose an extension to Stone's test which allows for covariate adjustment via a log-linear model, mu i = Ei lambda i exp (sigma jp = 1 xij beta j), where the xij are the values of each of p explanatory variables in each of the n regions, and the beta j are unknown regression parameters. Our methods are illustrated using data on the incidence of stomach cancer near two municipal incinerators. |
| Databáze: | OpenAIRE |
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