Development, Application, and Testing of Multi-pollutant Statistical Models and Methods.
HEI has had a long term commitment, and record of success, in the examination of key statistical challenges such as model selection, and development, application, and testing of cutting edge statistical models and methods to analyze the relation between air pollution and health. Several HEI projects have included strong methodologic components; in addition, HEI has funded studies aimed at methods development through specific RFAs and other mechanisms. In as much as air pollution science is concerned with testing whether it is possible to parse relatively small associations of health and air pollution in the context of myriad other variables, the need for development and improvement in methods continues to occupy a very important place in HEI’s future research plans.
HEI published three studies to develop and apply advanced statistical methods for multi-pollutant research. Please see RFA 09-1 for more information. Another study developed methods for causal inference methods applied to accountability research.