Simulation validation using Causal Inference Theory with morphological constraints

We present an approach for the validation of complex simulation based on the structured elicitation of expert knowledge. Knowledge capture is based on the technique of Morphological Analysis, which is used to capture expert information on causal linkages and constraints in a systems and its simulation representation. This information is combined with Causal Inference Theory arguments to develop assertions about statistical dependency relations that should exist in both system and simulation. Causal Techniques for conducting these tests, which include the elicited constraint information are described. Overviews of Morphological Analysis, Causal Inference Theory and Statistical Testing Approaches are provided in the context of a Bayesian simulation of an example problem.