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...

Full description

Saved in:
Bibliographic Details
Published in:Communications in statistics. Theory and methods Vol. 54; no. 22; pp. 7105 - 7122
Main Authors: Li, Zhi, Li, Zhiming, Tian, Rui, Li, Zhengqi
Format: Journal Article
Language:English
Published: Philadelphia Taylor & Francis 17.11.2025
Taylor & Francis Ltd
Subjects:
Blocked designs
blocked general minimum lower-order confounding
computer algorithm
ISSN:0361-0926, 1532-415X
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0361-0926
1532-415X
DOI:10.1080/03610926.2025.2467196