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On constructing general minimum lower order confounding two-level block designs

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  • Sheng-Li Zhao
  • Qing Sun

Abstract

In practice, to reduce systematic variation and increase precision of effect estimation, a practical design strategy is then to partition the experimental units into homogeneous groups, known as blocks. It is an important issue to study the optimal way on blocking the experimental units. Blocked general minimum lower order confounding (B1-GMC) is a new criterion for selecting optimal block designs. The paper considers the construction of optimal two-level block designs with respect to the B1-GMC criterion. By utilizing doubling theory and MaxC2 design, some optimal block designs with respect to the B1-GMC criterion are obtained.

Suggested Citation

  • Sheng-Li Zhao & Qing Sun, 2017. "On constructing general minimum lower order confounding two-level block designs," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(3), pages 1261-1274, February.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:3:p:1261-1274
    DOI: 10.1080/03610926.2015.1014112
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    Cited by:

    1. Qianqian Zhao & Shengli Zhao, 2019. "Some results on two-level regular designs with multi block variables containing clear effects," Statistical Papers, Springer, vol. 60(5), pages 1569-1582, October.

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