A three-class variance swapping technique for simulation experiments

The 2(k) factorial design is widely used in simulation experiments involvin g several factors in which the mean effect, the main effects, and the inter action effects of these factors are estimated. Previous research has differ entiated all effects into effects of interest and no interest. Traditional variance swapping techniques are then used to increase the accuracy of the estimators of the effects of interest. This article allows one to make a fi ner distinction among levels of interest. We allow the effects to be divide d into three groups, say, those of primary interest, secondary interest, an d little interest. We do this by dividing the class previously labelled as being of no interest into subclasses of "secondary interest" and "little in terest". Then we reallocate the relative variances of the estimators of the effects in the two subclasses. We call this approach a three-class varianc e swapping technique. (C) 1998 Elsevier Science B.V. All rights reserved.