@article {wu_simultaneous_2004,
	title = {Simultaneous inference for longitudinal data with detection limits and covariates measured with errors, with application to AIDS studies},
	journal = {Statistics in Medicine},
	volume = {23},
	number = {11},
	year = {2004},
	month = {jun},
	pages = {1715{\textendash}1731},
	abstract = {In AIDS studies such as HIV viral dynamics, statistical inference is often complicated because the viral load measurements may be subject to left censoring due to a detection limit and time-varying covariates such as CD4 counts may be measured with substantial errors. Mixed-effects models are often used to model the response and the covariate processes in these studies. We propose a unified approach which addresses the censoring and measurement errors simultaneously. We estimate the model parameters by a Monte-Carlo EM algorithm via the Gibbs sampler. A simulation study is conducted to compare the proposed method with the usual two-step method and a naive method. We find that the proposed method produces approximately unbiased estimates with more reliable standard errors. A real data set from an AIDS study is analysed using the proposed method. Copyright {\textcopyright} 2004 John Wiley \& Sons, Ltd.},
	keywords = {EM algorithm, Gibbs sampler, HIV, mixed-effects model},
	issn = {1097-0258},
	doi = {10.1002/sim.1748},
	url = {http://onlinelibrary.wiley.com/doi/10.1002/sim.1748/abstract},
	author = {WU, LANG}
}
