Glucose minimal model parameters are commonly estimated by applying weighted nonlinear least squares to each individual subject's data. Sometimes, parameter precision is not satisfactory, especially in "data poor" conditions. In this 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. In particular, we compared the performance of two likelihood approximation methods to estimate nonlinear mixed-effects model parameters, i.e. the first-order conditional estimation (FOCE) and the Laplace approximation (Laplace) methods. The results show that nonlinear mixed-effects population modeling using the FOCE approximation can be successfully used in order to accurately estimate individual minimal model parameters.

Identification of IVGTT minimal glucose model by nonlinear mixed-effects approaches

DENTI, PAOLO;BERTOLDO, ALESSANDRA;COBELLI, CLAUDIO
2006

Abstract

Glucose minimal model parameters are commonly estimated by applying weighted nonlinear least squares to each individual subject's data. Sometimes, parameter precision is not satisfactory, especially in "data poor" conditions. In this 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. In particular, we compared the performance of two likelihood approximation methods to estimate nonlinear mixed-effects model parameters, i.e. the first-order conditional estimation (FOCE) and the Laplace approximation (Laplace) methods. The results show that nonlinear mixed-effects population modeling using the FOCE approximation can be successfully used in order to accurately estimate individual minimal model parameters.
2006
Proceeding of Annual International Conference of the IEEE Engineering in medicine and biology society
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/145836
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