Bayesian analysis of minimal model under the insulin-modified IVGTT  

作　　者：Yi Wang Kent M. Eskridge Andrzej T. Galecki 

机构地区：[1]University of Michigan [2]University of Nebraska-Lincoln

出　　处：《Health》2010年第3期188-194,共7页健康（英文）

摘　　要：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.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.

关 键 词：MINIMAL Model BAYESIAN Analysis IVGTT Nonlinear Mixed-Effects Modeling ODE 

分 类 号：O1[理学—数学]