A sensitivity analysis method widely used to screen factors in models of large dimensionality is the design proposed by Morris. The Morris method deals efficiently with models containing hundreds of input factors without relying on strict assumptions about the model, such as for instance additivity or monotonicity of the model input-output relationship. The Morris method is simple to understand and implement, and its results are easily interpreted. Furthermore, it is economic in the sense that it requires a number of model evaluations that is linear in the number of model factors. The method can be regarded as global as the final measure is obtained by averaging a number of local measures (the elementary effects), computed at different points of the input space.