Sensitivity Analysis for Unmeasured Confounding and Nonignorable Missingness

In observational studies and clinical trials, the sensitivity analysis has become a routine procedure for statistical data analysis. The sensitivity analysis is particularly important for two types of problems: unmeasured confounding and nonignorable missing data, in which some unverified assumptions are imposed in the statistical protocol. This workshop will present the basic set-up and statistical methods for conducting sensitivity analysis, especially in these two types of problems. Some state-of-the-art motivating examples and programming softwares will also be introduced.

ACCREDITATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences is accredited by the ACCME to provide continuing medical education for physicians.

CERTIFICATION: The University at Buffalo Jacobs School of Medicine and Biomedical Sciences designates this live activity for a maximum of 2.0 AMA PRA Category 1 Credit(s)TM.  Physicians should claim only the credit commensurate with the extent of their participation in the activity.

CREDIT: This program is supported by the National Center for Advancing Translational Sciences of the National Institutes of Health under award number UL1TR001412.