More on our efforts to expose human experimentation that makes no sense if the EPA is telling the truth about air pollution.
Here is another public release that also discusses congressional activities.
http://www.prnewswire.com/news-releases/epa-experiments-seek-to-harm-sick-patients-states-association-of-american-physicians-and-surgeons-254903651.html
An Essay on the problems with EPA Junk Science and unethical research.
Even Cass Sunstein is admitting the evidence for PM 2.5 is dicey (see this week’s Science, http://www.sciencemag.org/content/344/6181/257.summary ).
He says:
“In the last 40 years, the evidence that has led to revisions of the U.S. National Ambient Air Quality Standards has come mainly from observational studies aimed at estimating an exposure-response relation (2). But associational approaches to inferring causal relations can be highly sensitive to the statistical model and covariates used to adjust for confounding. Indeed, the U.S. government itself has drawn attention to the “uncertainty in the reduction of premature deaths associated with reduction in particulate matter” (3).
There is a growing consensus in economics, political science, statistics, and other fields that the associational or regression approach to inferring causal relations—on the basis of adjustment with observable confounders—is unreliable in many settings”
In looking at the studies on TSP (total suspended particles) he finds:
“Of the 12 regression estimates, two show a significant positive association between TSPs and mortality, two perversely show a significant negative association, and the remaining eight would be judged statistically insignificant at conventional levels. In this setting, the addition of covariates causes a reduction in the coefficients, but this is not generalizable to other studies, as bias due to confounding can go in either direction. Overall, it is apparent that with these data and the available covariates, the association between TSPs and mortality rates varies widely within a year across models and within a model across years”.
Of course they go on to propose a new method, but at least they are formally recognizing the huge limitations of the current approach.