Several Crossed Treatment Factors

Abstract

When an experiment involves three or more treatment factors, the presence of high order interactions must be considered. Completely randomized designs for such factorial experiments form the topic of this chapter. Several different models are examined and, in the case of equal sample sizes per treatment combination, formulas for confidence intervals and hypothesis tests are developed. Since the total number of treatment combinations can become large, methods are presented for analyzing experiments with a single observation per treatment combination and no degrees of freedom for error. The concepts introduced in this chapter are illustrated through a real experiment and with the use of SAS and R software.