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• W1983002351 abstract "Pharmacokinetic/pharmacodynamic phenotypes are identified using nonlinear random effects models with finite mixture structures. A maximum a posteriori probability estimation approach is presented using an EM algorithm with importance sampling. Parameters for the conjugate prior densities can be based on prior studies or set to represent vague knowledge about the model parameters. A detailed simulation study illustrates the feasibility of the approach and evaluates its performance, including selecting the number of mixture components and proper subject classification." @default.
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• W1983002351 date "2009-10-01" @default.
• W1983002351 modified "2023-10-14" @default.
• W1983002351 title "Population pharmacokinetic/pharmacodynamic mixture models via maximum a posteriori estimation" @default.
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• W1983002351 doi "https://doi.org/10.1016/j.csda.2009.04.017" @default.
• W1983002351 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/2743512" @default.
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