Classification and regression trees for epidemiologic research: an air pollution example (18 page pdf, Katherine Gass, Mitch Klein,Howard H Chang, W Dana Flanders, Matthew J Strickland, Environmental Health, Mat. 13, 2014)
Today we review a paper that looks at ways that statistical regression trees may be used to improve the estimates of how much “confounding” [mix up (something) with something else so that the individual elements become difficult to distinguish.] goes on when there are multiple air pollutants that may or may not combine and augment each other in producing the health impacts that they collectively cause. The authors used over10 years of daily data for CO, NO2, O3, and PM2.5. Interestingly, they suggest that this same approach may be useful in nutrition.
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