Data from: A problem of bias and response heterogeneity, in Standing With Giants: A Collection of Public Health Essays in Memoriam to Dr. Elizabeth M. Whelan
Young, S. Stanley; Obenchain, Robert L.; Lambert, Christophe G. (2017), Data from: A problem of bias and response heterogeneity, in Standing With Giants: A Collection of Public Health Essays in Memoriam to Dr. Elizabeth M. Whelan, Dryad, Dataset, https://doi.org/10.5061/dryad.0kn60
There is extensive literature on the question, “Does air quality have health effects?” For example, Google Scholar gives 199,000 hits for (“mortality” and “air pollution”). See Health Effects Institute (2010) and editorial by Brauer and Mancini (2014), for example. One paper that appeared in 1993 has over 6,000 citations. The vast majority of these papers find a positive association between air quality health effects (death). A few papers make the case that if potential bias is carefully taken into account then there is no association between air quality and deaths, e.g. Chay et al. (2003), Enstrom (2005), Janes et al. (2007), Greven et al. (2011), Cox et al. (2013). Clearly the weight of evidence is for a positive association, but for any particular type of claim, logically it takes only one true negative to negate all the positives associations with respect to causation for that claim. A real, causative claim should always be detected in a well-designed and properly run experiment. What are some of the factors that lead to these discordant literature results?