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Mixed Effect Models: Design of Clinical Studies

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After a short discussion of commonalities between the mixed effect models and the Bayesian setting I define two design problems. The first one is related to the estimation of the population parameters and is often used in comparison of different treatments or in dose response studies. The necessity to estimate individual parameters (for a specific experimental unit like a clinical center or even a patient) leads to another optimization problem. I compare various criteria of optimality for both settings and derive elemental information matrices for various special cases. The latter allows to apply the standard machinery of optimal design of experiments.

This talk is part of the Isaac Newton Institute Seminar Series series.

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