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...

Descripción completa

Detalles Bibliográficos

Publicado en:	American Journal of Public Health Vol. 106; no. 7; pp. 1227 - 1231
Autores principales:	Lash, Timothy L., Fox, Matthew P., Cooney, Darryl, Yun Lu, Forshee, Richard A.
Formato:	Artículo
Publicado:	American Public Health Association Jul2016
Materias:	United States. Food & Drug Administration Decision making Medical research Experimental design Research methodology Quality assurance Data analysis Research bias Standards
Acceso en línea:	Ver este registro en EBSCOhost