Statistically designed experiments, particularly fractional factorial designs, are key tools to use when the object is to screen a large number of variables in order to identify those with the most influence.

Inaccurate data points are particularly troublesome in the analysis of unreplicated factorial experiments, but new techniques allow investigators to overcome this difficulty.

Variable-selection regression methods are oriented towards selecting a single model as the vehicle for further inferences. The appropriate inference about variables not included is unclear - the conclusion that they have ...

Some important implications and statistical details of Box and Meyer's formal approach to the analysis of unreplicated fractional factorial experiments.

How to pinpoint the most likely explanation for the results of unreplicated fractional factorial experiments.