TITLE:
Bayesian analysis of minimal model under the insulin-modified IVGTT
AUTHORS:
Yi Wang, Kent M. Eskridge, Andrzej T. Galecki
KEYWORDS:
Minimal Model; Bayesian Analysis; IVGTT; Nonlinear Mixed-Effects Modeling; ODE
JOURNAL NAME:
Health,
Vol.2 No.3,
March
23,
2010
ABSTRACT: A Bayesian analysis of the minimal model was proposed where both glucose and insulin were analyzed simultaneously under the insulin-modified intravenous glucose tolerance test (IVGTT). The resulting model was implemented with a nonlinear mixed-effects modeling setup using ordinary differential equations (ODEs), which leads to precise estimation of population parameters by separating the inter- and intra-individual variability. The results indicated that the Bayesian method applied to the glucose-insulin minimal model provided a satisfactory solution with accurate parameter estimates which were numerically stable since the Bayesian method did not require approximation by linearization.