Statistical models of test taker behavior underlie many modern psychometric methodologies. An advantage of this approach is that it supports studies where simulated test taker responses are generated according to the particular statistical model in order to explore model properties. To the extent that such models fail to capture important aspects of real test takers' responses, the predictive utility of such simulation studies may be compromised. In this paper a methodology is explored that builds simulated test taker responses using information distilled from the responses of real test takers. This approach proved effective in capturing some aspects of test taker behavior that simpler models failed to incorporate.