TY - JOUR
T1 - A refined parameter estimating approach for HIV dynamic model
AU - Lu, Tao
AU - Huang, Yangxin
AU - Wang, Min
AU - Qian, Feng
PY - 2014/8
Y1 - 2014/8
N2 - HIV dynamic models, a set of ordinary differential equations (ODEs), have provided new understanding of the pathogenesis of HIV infection and the treatment effects of antiviral therapies. However, to estimate parameters for ODEs is very challenging due to the complexity of this nonlinear system. In this article, we propose a comprehensive procedure to deal with this issue. In the proposed procedure, a series of cutting-edge statistical methods and techniques are employed, including nonparametric mixed-effects smoothing-based methods for ODE models and stochastic approximation expectation-maximization (EM) approach for mixed-effects ODE models. A simulation study is performed to validate the proposed approach. An application example from a real HIV clinical trial study is used to illustrate the usefulness of the proposed method.
AB - HIV dynamic models, a set of ordinary differential equations (ODEs), have provided new understanding of the pathogenesis of HIV infection and the treatment effects of antiviral therapies. However, to estimate parameters for ODEs is very challenging due to the complexity of this nonlinear system. In this article, we propose a comprehensive procedure to deal with this issue. In the proposed procedure, a series of cutting-edge statistical methods and techniques are employed, including nonparametric mixed-effects smoothing-based methods for ODE models and stochastic approximation expectation-maximization (EM) approach for mixed-effects ODE models. A simulation study is performed to validate the proposed approach. An application example from a real HIV clinical trial study is used to illustrate the usefulness of the proposed method.
KW - dynamic model
KW - nonlinear mixed-effects model
KW - nonparametric mixed-effects model; SAEM
UR - http://www.scopus.com/inward/record.url?scp=84899965058&partnerID=8YFLogxK
U2 - 10.1080/02664763.2014.885001
DO - 10.1080/02664763.2014.885001
M3 - Article
AN - SCOPUS:84899965058
SN - 0266-4763
VL - 41
SP - 1645
EP - 1657
JO - Journal of Applied Statistics
JF - Journal of Applied Statistics
IS - 8
ER -