Uncertainty is an integral part of risk assessment of complex engineering systems, such as nuclear power plants and space crafts. The aim of sensitivity analysis is to identify the contribution of the uncertainty in model inputs to the uncertainty in the model output. In this study, a new importance measure that characterizes the influence of the entire input distribution on the entire output distribution was proposed. It represents the expected deviation of the cumulative distribution function (CDF) of the model output that would be obtained when one input parameter of interest were known. The applicability of this importance measure was tested with two models, a nonlinear nonmonotonic mathematical model and a risk model. In addition, a comparison of this new importance measure with several other importance measures was carried out and the differences between these measures were explained.