Glucose minimal model parameters are commonly estimated by applying weighted nonlinear least squares separately to each subject's data. Because of the model's nonlinearity. the parameter precision of the single-compartment minimal model is not always satisfactory, especially in presence of a reduced sampling schedule. In the current work, the use of population analysis through nonlinear mixed effects models is evaluated and its performance tested against the parameter estimates obtained by the standard individual approach through weighted nonlinear least squares.

The glucose minimal model: Population vs individual parameter estimation

BERTOLDO, ALESSANDRA;COBELLI, CLAUDIO
2006

Abstract

Glucose minimal model parameters are commonly estimated by applying weighted nonlinear least squares separately to each subject's data. Because of the model's nonlinearity. the parameter precision of the single-compartment minimal model is not always satisfactory, especially in presence of a reduced sampling schedule. In the current work, the use of population analysis through nonlinear mixed effects models is evaluated and its performance tested against the parameter estimates obtained by the standard individual approach through weighted nonlinear least squares.
2006
IFAC Proceedings Volumes
9783902661180
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/2530267
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