Some results on constructing three-level blocked designs with general minimum lower-order confounding - Li, Zhi; Li, Zhiming; Tian, Rui; Li, Zhengqi (Communications in statistics. Theory and methods, 2025)
Blocked designs are widely used in experimental situations when the experimental units are not homogeneous. This article introduces the blocked general minimum lower-order confounding (B 1 -GMC) criterion for selecting optimal three-level blocked designs. Some properties of three-level B 1 -GMC designs are provided in terms of their complementary sets. We obtain a systematic theory on constructing three-level B 1 -GMC designs. Several efficient algorithms for finding three-level B 1 -GMC designs are provided and implemented by Python. For application, B 1 -GMC designs with 27-, 81- and 243-run, respectively, are tabulated.