Sensitivity analysis screening methods aim to isolate the most important factors in experiments involving a large number of significant factors and interactions.

This paper extends the one-factor-at-a-time screening method proposed by Morris. The new method, in addition to the `overall' sensitivity measures already provided by the traditional Morris method, offers estimates of the two-factor interaction effects. The number of model evaluations required is O(k2), where k is the number of model input factors.

The efficient sampling strategy in the parameter space is based on concepts of graph theory and on the solution of the `handcuffed prisoner problem'.