Generalized semiparametric varying-coefficient model for longitudinal data with applications to adaptive treatment randomizations.

TitleGeneralized semiparametric varying-coefficient model for longitudinal data with applications to adaptive treatment randomizations.
Publication TypeJournal Article
Year of Publication2017
AuthorsQi L, Sun Y, Gilbert PB
JournalBiometrics
Volume73
Issue2
Pagination441-451
Date Published2017 06
ISSN1541-0420
KeywordsComputer Simulation, Humans, Least-Squares Analysis, Random Allocation, Research Design
Abstract

This article investigates a generalized semiparametric varying-coefficient model for longitudinal data that can flexibly model three types of covariate effects: time-constant effects, time-varying effects, and covariate-varying effects. Different link functions can be selected to provide a rich family of models for longitudinal data. The model assumes that the time-varying effects are unspecified functions of time and the covariate-varying effects are parametric functions of an exposure variable specified up to a finite number of unknown parameters. The estimation procedure is developed using local linear smoothing and profile weighted least squares estimation techniques. Hypothesis testing procedures are developed to test the parametric functions of the covariate-varying effects. The asymptotic distributions of the proposed estimators are established. A working formula for bandwidth selection is discussed and examined through simulations. Our simulation study shows that the proposed methods have satisfactory finite sample performance. The proposed methods are applied to the ACTG 244 clinical trial of HIV infected patients being treated with Zidovudine to examine the effects of antiretroviral treatment switching before and after HIV develops the T215Y/F drug resistance mutation. Our analysis shows benefits of treatment switching to the combination therapies as compared to continuing with ZDV monotherapy before and after developing the 215-mutation.

DOI10.1111/biom.12626
Alternate JournalBiometrics
PubMed ID27918612
PubMed Central IDPMC5459686
Grant ListUM1 AI068634 / AI / NIAID NIH HHS / United States
R37 AI054165 / AI / NIAID NIH HHS / United States
U01 AI038858 / AI / NIAID NIH HHS / United States
U01 AI068636 / AI / NIAID NIH HHS / United States
U01 AI068634 / AI / NIAID NIH HHS / United States
UM1 AI068636 / AI / NIAID NIH HHS / United States