An efficient screening methodology for a priori assessed non-influential factors

The choice of which factors to choose to vary in a simulation to effect a change in the measure of interest is difficult. Many factors are a priori judged not to effect the measure of interest. There is often no subsequent analysis of whether this judgment is valid or not. The proposed methodology outlines a sequence of limited runs to assess the accuracy of the a priori belief of noninfluential factors. These runs can either identify if an influential factor(s) has been omitted or confirm a priori beliefs. Executing these sequences of runs before focusing on the suspected influential factors can contribute to subsequent analysis by confirming that suspected noninfluential factors do not significantly impact the measure of interest. An example of the methodology using an agent based model is presented.