Optimal Blocking Schemes for 2nand 2n—pDesigns

Sun, Danfeng; Wu, C. F. J.; Chen, Youyi

doi:10.1080/00401706.1997.10485121

Cited by 31 publications

(11 citation statements)

References 9 publications

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“…Sun et al . () approached the related problem of constructing fractional factorial designs with one blocking factor by starting with a 2 n − t ‐factorial, with a high ranking according to aberration, and investigating allocation of the treatment combinations to blocks to maximize the number of estimable main effects and two‐factor interactions.…”

Section: Fractional Designsmentioning

confidence: 99%

Construction of Row–Column Factorial Designs

Godolphin

2018

Journal of the Royal Statistical Society Series B: Statistical Methodology

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Summary The arrangement of 2n‐factorials in row–column designs to estimate main effects and two‐factor interactions is investigated. Single‐replicate constructions are given which enable estimation of all main effects and maximize the number of estimable two‐factor interactions. Constructions and guidance are given for multireplicate designs in single arrays and in multiple arrays. Consideration is given to constructions for 2n−t fractional factorials.

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Section: Fractional Designsmentioning

confidence: 99%

Construction of Row–Column Factorial Designs

Godolphin

2018

Journal of the Royal Statistical Society Series B: Statistical Methodology

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“…Blocking is a useful way to reduce the influence of these systematic sources of variation by arranging homogeneous experimental runs into groups. There are many recent studies on the optimal choices of blocking schemes for fractional factorial designs; see, among others, . However, real applications of blocked fractional factorial designs is limited in the biomedical science area.…”

Section: Follow‐up Three‐level Experimentsmentioning

confidence: 99%

Application of fractional factorial designs to study drug combinations

Jaynes

et al. 2012

Statistics in Medicine

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Herpes simplex virus type 1 (HSV-1) is known to cause diseases of various severities. There is increasing interest to find drug combinations to treat HSV-1 by reducing drug resistance and cytotoxicity. Drug combinations offer potentially higher efficacy and lower individual drug dosage. In this paper, we report a new application of fractional factorial designs to investigate a biological system with HSV-1 and six antiviral drugs, namely, Interferon-alpha, Interferon-beta, Interferon-gamma, Ribavirin, Acyclovir, and TNF-alpha. We show how the sequential use of two- and three-level fractional factorial designs can screen for important drugs and drug interactions, as well as determine potential optimal drug dosages through the use of contour plots. Our initial experiment using a two-level fractional factorial design suggests that there is model inadequacy and drug dosages should be reduced. A follow-up experiment using a blocked three-level fractional factorial design indicates that TNF-alpha has little effect and HSV-1 infection can be suppressed effectively by using a right combination of the other five antiviral drugs. These observations have practical implications in the understanding of antiviral drug mechanism that can result in better design of antiviral drug therapy.

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“…For 2 designs D and D ∗ with a compound criterion including g criteria, D is said to be dominated by D ∗ or inadmissible if D ∗ is better than D for at least one of the g criteria and strictly better than D for at least one of the g criteria. If there exists no design that can dominate D , then D is called the admissible design . A method to handle dual‐criterion situation is simply adding the 2 criteria (after they are appropriately standardized) and selecting a design that optimizes this sum.…”

Section: Algorithm and Approximate Methodsmentioning

confidence: 99%

Robust designs with high projection efficiency

Lin

2018

Quality & Reliability Eng

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Alphabetic optimality criteria, such as the D, A, and I criteria, require specifying a model to select optimal designs. They are not model‐free, and the designs obtained by them may not be robust. Recently, many extensions of the D and A criteria have been proposed for selecting robust designs with high estimation efficiency. However, approaches for finding robust designs with high prediction efficiency are rarely studied in the literature. In this paper, we propose a compound criterion and apply the coordinate‐exchange 2‐phase local search algorithm to generate robust designs with high estimation, high prediction, or balanced estimation and prediction efficiency for projective submodels. Examples demonstrate that the designs obtained by our method have better projection efficiency than many existing designs.

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Optimal Blocking Schemes for 2nand 2n—pDesigns

Cited by 31 publications

References 9 publications

Construction of Row–Column Factorial Designs

Construction of Row–Column Factorial Designs

Application of fractional factorial designs to study drug combinations

Robust designs with high projection efficiency

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