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

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 desi...

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Vydané v:Communications in statistics. Theory and methods Ročník 54; číslo 22; s. 7105 - 7122
Hlavní autori: Li, Zhi, Li, Zhiming, Tian, Rui, Li, Zhengqi
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Philadelphia Taylor & Francis 17.11.2025
Taylor & Francis Ltd
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ISSN:0361-0926, 1532-415X
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2025.2467196