SciMetrika is pleased to announce that the American Journal of Public Health has, for the first time, accepted a paper for publication from our team. Titled, “Quantitative bias analysis in regulatory settings,” the SciMetrika-authored paper will appear as a Commentary in an upcoming edition of AJPH.
Non-randomized studies play an essential role in the post-market surveillance activities of the U.S. Food and Drug Administration (FDA). In many cases, however, FDA must act on the basis of imperfect data. Systematic errors can lead to inaccurate inferences, so it is critical to develop analytic methods that quantify uncertainty and bias, and to ensure that these methods are implemented when needed. Quantitative bias analysis is an overarching term for methods that estimate quantitatively the direction, magnitude, and uncertainty associated with systematic errors influencing measures of associations. Given this background, the FDA has sponsored this collaborative project to develop tools intended to better quantify the uncertainties associated with post-market surveillance studies used in regulatory decision-making.
Congratulations to our team for work well done.