Quantitative Bias Analysis in Regulatory Settings.

Nonrandomized studies are essential in the postmarket activities of the US Food and Drug Administration, which, however, must often 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 bia...

Full description

Bibliographic Details

Published in:	American Journal of Public Health Vol. 106; no. 7; pp. 1227 - 1231
Main Authors:	Lash, Timothy L., Fox, Matthew P., Cooney, Darryl, Yun Lu, Forshee, Richard A.
Format:	Article
Published:	American Public Health Association Jul2016
Subjects:	United States. Food & Drug Administration Decision making Medical research Experimental design Research methodology Quality assurance Data analysis Research bias Standards
Online Access:	View this record in EBSCOhost