Three-level blocked regular designs with general minimum lower order confounding

Yanfei Wang, Zhiming Li and Runchu Zhang

Communications in Statistics - Theory and Methods, 2020, vol. 49, issue 10, 2498-2513

Abstract: When the experimental units are heterogeneous, blocking the units into groups is a crucial way. In this paper we consider the selection of optimal three-level blocked regular designs. A blocked aliased component-number pattern (B-ACNP) is introduced and a blocked general minimum lower order confounding (B1-GMC) criterion for selecting three-level blocked designs is proposed. Some relations of this criterion with other existing criteria are given. Some results of constructing three-level B1-GMC designs are obtained. For comparison, all the B1-GMC, B-GMC and four MA-type 3n−m:3p designs with 27, 81 and 243 runs, n=4,5,…,10 and p = 1, 2, 3 are tabulated.

Date: 2020
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DOI: 10.1080/03610926.2019.1576891

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