Resumen

CASTANEDA-LOPEZ, María Eugenia  y  LOPEZ-RIOS, Víctor Ignacio. An Optimal Design Criterion for Within-Individual Covariance Matrices Discrimination and Parameter Estimation in Nonlinear Mixed Effects Models. Rev.Colomb.Estad. [online]. 2020, vol.43, n.2, pp.127-141.  Epub 05-Dic-2020. ISSN 0120-1751.  https://doi.org/10.15446/rce.v43n2.81938.

In this paper, we consider the problem of finding optimal population designs for within-individual covariance matrices discrimination and parameter estimation in nonlinear mixed effects models. A compound optimality criterion is provided, which combines an estimation criterion and a discrimination criterion. We used the D-optimality criterion for parameter estimation, which maximizes the determinant of the Fisher information matrix. For discrimination, we propose a generalization of the T-optimality criterion for fixed-effects models. Equivalence theorems are provided for these criteria. We illustrated the application of compound criteria with an example in a pharmacokinetic experiment.

Palabras clave : Compound criteria; D-optimality; Mixed effects models; Optimal designs; T-optimality.

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