This paper develops two procedures for screening a set of normal populations with unknown moments in order that the final subset of selected populations satisfies the following requirements involving the user specified parameters P*, δ, and m: With probability at least P*, the selected subset will contain a population whose mean lies less than the distance δ from the largest mean. Although the size of the selected subset is random, at most m populations will finally be chosen, where m is usually taken small enough to reserve adequate resources for a more intensive follow-up study. The exact procedure VE is a two-stage random sampling scheme that is designed to compare transient or steady-state simulation models based on independent replications of each model. The heuristic procedure VS is a modification of VE that is designed to compare steady-state simulation models based on a single prolonged run of each model. A complete justification is given for VE together with tables of the constants required by both procedures and an algorithm for computing these constants. Experimental results are summarized to gauge the robustness of VE against departures from normality and to evaluate the performance of VS on several types of stationary stochastic processes.
