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Maximin D-Optimal Designs for Longitudinal Mixed Effects Models
Mario J. N. M. Ouwens, Frans E. S. Tan and Martijn P. F. Berger
Vol. 58, No. 4 (Dec., 2002), pp. 735-741
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/3068515
Page Count: 7
You can always find the topics here!Topics: Design efficiency, Maximin, Polynomials, Parametric models, Mathematical vectors, Statistical variance, Statistical models, Matrices, Linear regression, Design evaluation
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In this article, the optimal selection and allocation of time points in repeated measures experiments is considered. D-optimal cohort designs are computed numerically for the first- and second-degree polynomial models with random intercept, random slope, and first-order autoregressive serial correlations. Because the optimal designs are locally optimal, it is proposed to use a maximin criterion. It is shown that, for a large class of symmetric designs, the smallest relative efficiency over the model parameter space is substantial.
Biometrics © 2002 International Biometric Society