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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
Biometrics
Vol. 58, No. 4 (Dec., 2002), pp. 735-741
Stable URL: http://www.jstor.org/stable/3068515
Page Count: 7
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Maximin D-Optimal Designs for Longitudinal Mixed Effects Models
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Abstract

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.

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