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Overcoming Bias Commenter's avatar

Causality likely sometimes goes either way, but given the costs of doing medical studies or anything involving bigger surveys one needs it is likely that funding is needed before the study. Running a tiny pilot might be possible and indeed lead to selecting a favorable source of funding, but here it might be just as much researcher bias - if the researcher "knows" what the outcome is likely to be he might search funding in the appropriate direction, hinting at it.

Calling for more rigorous, verified research is a nice idea, but in practice it may be hard to do in many fields. What is a rigorous social survey?

In a clear case of bias, I'm now noticing lots of new papers on publication bias. PLoS Medicine has two interesting ones (and a commentary):

http://medicine.plosjournal..."Relationship between Funding Source and Conclusion among Nutrition-Related Scientific Articles"

http://medicine.plosjournal..."Ghost Authorship in Industry-Initiated Randomised Trials"

http://medicine.plosjournal..."Authors, Ghosts, Damned Lies, and Statisticians"

The first paper demonstrates funding bias in nutrition. The odds ratio was 7.61, and no unfavorable findings were reported at all from the industry funded studies (vs. 37% for the rest). The second shows that a lot of ghost authors, mostly statisticians, appear in industry sponsored papers.

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Overcoming Bias Commenter's avatar

seeing that a paper was funded by Acme Corporation tells us to adjust for funding bias, but if it was funded by the NIH we don't know if there is a bias or not.

Maybe a historical study is the way to go here? Take issues that are dead and settled (such as "radioactivity is bad for you", "asbestos is causes cancer" and even "smoking causes lung cancer"), and see what biases were induced by various funding bodies when these issues were "hot"?

But I don't see how we can easily generalise from history, seeing the miriads of research policies and governments that have changed over the years since then. Its very possible that public funding is biases in different ways, for different issues, at different times.

Maybe the best is to accept that there will be a bias, that we can't overcome it a priori, and just call for more rigorous, verified research and let the scientific method work its magic? The question of bias is the most usefull to highlight those areas where this extra research will be needed.

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