id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-292234-8o4kfhe1	Cox, Louis Anthony	Should air pollution health effects assumptions be tested? Fine particulate matter and COVID-19 mortality as an example	2020-09-02		.txt	text/plain	8108	325	40	One purpose of this paper is to discuss and illustrate how nonparametric and graphical (Bayesian network) methods can help to implement this approach in practice, taking as an illustrative example the question of whether a data set provides evidence that past levels of exposure to fine particulate matter (PM2.5) air pollution increase risks of COVID-19-associated mortality. The WoE approach does not require that causal judgments have more precise conceptual or operational meanings (e.g., distinguishing between necessary, sufficient, or contributing causes; or between direct and indirect effects; or providing an explicit philosophical or logical basis for defining causal effect); or make unambiguous predictions (e.g., about whether or by how much reducing air pollution levels would reduce health risks, given levels of other causally relevant variables); or that such predictions be tested against data before the conclusions are accepted and used to make policy recommendations.	./cache/cord-292234-8o4kfhe1.txt	./txt/cord-292234-8o4kfhe1.txt