TY - JOUR
T1 - A semiparametric threshold model for censored longitudinal data analysis
AU - Li, J L
AU - Zhang, Wenyang
PY - 2011/6
Y1 - 2011/6
N2 - Motivated by an investigation of the relationship between blood pressure change and progression of microalbuminuria (MA) among individuals with type I diabetes, we propose a new semiparametric threshold model for censored longitudinal data analysis. We also study a new semiparametric Bayes information criterion-type criterion for identifying the parametric component of the proposed model. Cluster effects in the model are implemented as unknown fixed effects. Asymptotic properties are established for the proposed estimators. A quadratic approximation used to implement the estimation procedure makes the method very easy to implement by avoiding the computation of multiple integrals and the need for iterative algorithms. Simulation studies show that the proposed methods work well in practice. An illustration using the Wisconsin Diabetes Registry dataset suggests some interesting findings.
AB - Motivated by an investigation of the relationship between blood pressure change and progression of microalbuminuria (MA) among individuals with type I diabetes, we propose a new semiparametric threshold model for censored longitudinal data analysis. We also study a new semiparametric Bayes information criterion-type criterion for identifying the parametric component of the proposed model. Cluster effects in the model are implemented as unknown fixed effects. Asymptotic properties are established for the proposed estimators. A quadratic approximation used to implement the estimation procedure makes the method very easy to implement by avoiding the computation of multiple integrals and the need for iterative algorithms. Simulation studies show that the proposed methods work well in practice. An illustration using the Wisconsin Diabetes Registry dataset suggests some interesting findings.
UR - http://www.scopus.com/inward/record.url?scp=79960136346&partnerID=8YFLogxK
UR - http://dx.doi.org/10.1198/jasa.2011.tm10592
U2 - 10.1198/jasa.2011.tm10592
DO - 10.1198/jasa.2011.tm10592
M3 - Article
SN - 0162-1459
VL - 106
SP - 685
EP - 696
JO - Journal of the American Statistical Association
JF - Journal of the American Statistical Association
IS - 494
ER -