Minimally changed run sequences in factorial experiments

Arpan Bhowmik, Eldho Varghese, Seema Jaggi and Cini Varghese

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 15, 7444-7459

Abstract: Randomization of run sequences in factorial experiments may result in large number of changes in factor levels which will make the experimentation expensive, time-consuming and difficult. Experiments in which it is difficult to change the levels of factor(s) use of minimally changed run sequences may often be preferable to a random run sequence. In the present paper, we have developed method for obtaining minimally changed run sequences for factorial experiments. The general expression of factor-wise number of level changes for the developed minimally changed run sequences has also been obtained. A relationship has been established between the time count effect of a lower order factorial with minimally changed run sequences and that of a higher order factorial with minimally changed run sequences obtained through the lower order minimally changed run sequences. For providing a readymade solution to the end users, a SAS macro has also been developed for generating these minimally changed run sequences along with its parameters.

Date: 2017
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DOI: 10.1080/03610926.2016.1152490

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