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Abstract Details

Activity Number: 415
Type: Contributed
Date/Time: Tuesday, July 31, 2012 : 2:00 PM to 3:50 PM
Sponsor: SSC
Abstract - #305493
Title: Two-Step and Likelihood Methods for HIV Viral Dynamic Models with Covariate Measurement Errors and Missing Data
Author(s): Wei Liu*+
Companies: York University
Address: 4700 Keele Street, Toronto, ON, M3J 1P3, Canada
Keywords: Cubic spline basis ; HIV viral dynamic model ; Longitudinal data ; Measurement error ; Missing data

HIV viral dynamic models have received much attention in the literature. Long-term viral dynamics may be modelled by semiparametric nonlinear mixed-effects (NLME) models, which incorporate large variation between subjects and auto-correlation within subjects and are flexible in modelling complex viral load trajectories. Time-dependent covariates may be introduced in the dynamic models to partially explain the between individual variations. In the presence of measurement errors and missing data in time-dependent covariates, we show that the commonly used two-step method may give approximately unbiased estimates but may under-estimate standard errors. We propose a two-stage bootstrap method to adjust the standard errors in the two-step method and a likelihood method.

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