@article {liu_two-step_2012,
	title = {Two-step and likelihood methods for HIV viral dynamic models with covariate measurement errors and missing data},
	journal = {Journal of Applied Statistics},
	volume = {39},
	number = {5},
	year = {2012},
	month = {may},
	pages = {963{\textendash}978},
	abstract = {HIV viral dynamic models have received much attention in the literature. Long-term viral dynamics may be modelled by semiparametric nonlinear mixed-effect models, which incorporate large variation between subjects and autocorrelation 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.},
	issn = {0266-4763},
	doi = {10.1080/02664763.2011.632404},
	url = {http://dx.doi.org/10.1080/02664763.2011.632404},
	author = {Liu, Wei and WU, LANG}
}
