Optimal cross-over designs for nonlinear mixed models using a first-order expansion |
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Authors: | Jixian Wang Byron Jones |
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Institution: | 1. Biostatistics and Statistical Reporting, WSJ103.5-10.14 Novartis Pharma AG, Lichtstrasse 35, Postfach CH-4002, Basel, Switzerland;2. Statistical Research and Consulting Centre, Pfizer Global Research and Development, Sandwich, CT13 9NJ Kent, UK |
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Abstract: | We consider the construction of optimal cross-over designs for nonlinear mixed effect models based on the first-order expansion. We show that for AB/BA designs a balanced subject allocation is optimal when the parameters depend on treatments only. For multiple period, multiple sequence designs, uniform designs are optimal among dual balanced designs under the same conditions. As a by-product, the same results hold for multivariate linear mixed models with variances depending on treatments. |
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Keywords: | Cross-over design First-order expansion Multivariate linear mixed models Nonlinear mixed effect models Optimal design |
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