TY - JOUR

T1 - Optimal step-type designs for comparing test treatments with a control

AU - Cheng, Ching Shui

AU - Majumdar, Dibyen

AU - Stufken, John

AU - Türe, Tahsin Erkan

N1 - Funding Information:
* Ching-Shui Cheng is Associate Professor, Department of Statistics, University of California, Berkeley, CA 94720. Dibyen Majumdar is As- sistant Professor, Department of Mathematics, Statistics, and Computer Science, University of Illinois, Chicago, IL 60680. John Stufken is Assistant Professor, Department of Statistics, University of Georgia, Athens, GA 30602. Tahsin Erkan Tiire is Associate Professor, Department of Mathematics and Computing, Sultan Qaboos University, Al-Khoudh, Muscat, Oman. The research was sponsored by National Science Foun- dation Grant DMS-8502784 and Air Force Office of Scientific Research Grant 85-0320.

PY - 1988/6

Y1 - 1988/6

N2 - The problem of obtaining A-optimal designs for comparing v test treatments with a control in b blocks of size k each is considered. A condition on the parameters (u, b, k) is identified for which optimal step-type designs can be obtained. Families of such designs are given. Methods of searching for highly efficient designs are proposed for situations in which it is difficult to determine an A-optimal design. Under the usual additive homoscedastic model, an A-optimal design minimizes the average variance of the least squares estimators of the control-test treatment comparisons. Majumdar and Notz (1983) gave a method for finding A-optimal designs. Their optimal designs can basically be of two types, using the terminology of Hedayat and Majumdar (1984): rectangular (R), in which every block has the same number of replications of the control, and step (5), in which some blocks contain the control t times and the others t + 1 times. Optimal R-type designs were studied by Hedayat and Majumdar (1985). Families of such designs, particularly when each block has one replication of the control, were given in that paper. In this article, we intend to study optimal S-type designs. Step-type designs are more complicated than rectangular-type designs; the latter are balanced incomplete block designs in the test treatments augmented by an equal number of controls in each block, but the former do not have such a simple characterization. Consequently, both the optimality and the construction of such designs are more involved.

AB - The problem of obtaining A-optimal designs for comparing v test treatments with a control in b blocks of size k each is considered. A condition on the parameters (u, b, k) is identified for which optimal step-type designs can be obtained. Families of such designs are given. Methods of searching for highly efficient designs are proposed for situations in which it is difficult to determine an A-optimal design. Under the usual additive homoscedastic model, an A-optimal design minimizes the average variance of the least squares estimators of the control-test treatment comparisons. Majumdar and Notz (1983) gave a method for finding A-optimal designs. Their optimal designs can basically be of two types, using the terminology of Hedayat and Majumdar (1984): rectangular (R), in which every block has the same number of replications of the control, and step (5), in which some blocks contain the control t times and the others t + 1 times. Optimal R-type designs were studied by Hedayat and Majumdar (1985). Families of such designs, particularly when each block has one replication of the control, were given in that paper. In this article, we intend to study optimal S-type designs. Step-type designs are more complicated than rectangular-type designs; the latter are balanced incomplete block designs in the test treatments augmented by an equal number of controls in each block, but the former do not have such a simple characterization. Consequently, both the optimality and the construction of such designs are more involved.

KW - A-optimal design

KW - Balanced incomplete block design

KW - Balanced treatment incomplete block design

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U2 - 10.1080/01621459.1988.10478620

DO - 10.1080/01621459.1988.10478620

M3 - Article

AN - SCOPUS:0000017569

VL - 83

SP - 477

EP - 482

JO - Journal of the American Statistical Association

JF - Journal of the American Statistical Association

SN - 0162-1459

IS - 402

ER -