Missing Data: Sensitivity Analysis

Abstract With the growing amount of methodology to analyze incomplete data, the awareness has grown that the results of such an analysis may be very sensitive to the modeling assumptions made, many of which are not, strictly speaking, verifiable from the data. Therefore, a lot of the later work is devoted to the exploration of such sensitivities. For both categorical as well as continuous outcomes…