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Some results on constructing three-level blocked designs with general minimum lower-order confounding

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  • Zhi Li
  • Zhiming Li
  • Rui Tian
  • Zhengqi Li

Abstract

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 (B1-GMC) criterion for selecting optimal three-level blocked designs. Some properties of three-level B1-GMC designs are provided in terms of their complementary sets. We obtain a systematic theory on constructing three-level B1-GMC designs. Several efficient algorithms for finding three-level B1-GMC designs are provided and implemented by Python. For application, B1-GMC designs with 27-, 81- and 243-run, respectively, are tabulated.

Suggested Citation

  • Zhi Li & Zhiming Li & Rui Tian & Zhengqi Li, 2025. "Some results on constructing three-level blocked designs with general minimum lower-order confounding," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 54(22), pages 7105-7122, November.
    • Handle: RePEc:taf:lstaxx:v:54:y:2025:i:22:p:7105-7122
    DOI: 10.1080/03610926.2025.2467196
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