Objective methods for analysing unreplicated factorial designs

There is not a method for analysing unreplicated factorial designs that performs well for various configurations of number and size of active effects. Moreover, the most popular tool that has been applied is informal and subjective. To overcome these drawbacks, this paper suggests a multiple testing to help practitioners making objective decisions and identifying active effects with a minimum number of additional runs for a wide range of active effects configurations. The selected methods are efficient and easy to implement by practitioners, including those who do not have a profound knowledge of statistics. Two examples from the literature exemplify and justify the proposed approach.