Review of random and group-screening designs

Experiments with real systems, but especially with simulated systems, may involve hundreds of factors. However, only a few factors are really important. Detecting these Important factors requires special designs such as random and group-screening de-signs. Random designs are simple, but they yield biased esti-mators. Group-screening is based on aggregation. The assumptions of group-screening are discussed in detail, and seem not very restrictive. References to applications of both design types are given.