"Much of the social and medical sciences depend on randomised control trials. But while this may be considered the foundational experimental method, a certain degree of bias inevitably arises in any trial; whether this is sample bias, selection bias, or measurement bias. This is important as the level of validity of a trial’s causal claims can be a matter of life or death. To Alexander Krauss, the scientific process is a complex human process, involving many actors required to take many unique decisions at many different stages, and so some degree of bias is unavoidable. This has implications for the reproducibility crisis, as variation between study outcomes becomes the norm, and one-to-one replication is not possible." "Taken together, researchers, practitioners, and policymakers need to become better aware of the broader range of biases facing trials. Journals need to begin to require researchers to outline in detail the assumptions, biases, and limitations in their studies. If researchers do not report this crucial information, practitioners and citizens will have to just rely on information and warning labels provided by policymakers, biopharmaceutical companies, and the like implementing the tested policies and selling the tested treatments." http://blogs.lse.ac.uk/impactofsoci...led-trials-inevitably-produce-biased-results/ "This blog post originally appeared under a different title on the Institute for New Economic Thinking blog. It is based on the author’s article, “Why all randomised controlled trials produce biased results”, published in the Annals of Medicine (DOI: 10.1080/07853890.2018.1453233)."