Mixed models: design of experiments
Seminar Room 1, Newton Institute
AbstractAfter 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.
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