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Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model
2006
Computational Statistics & Data Analysis
The reduction of viral load is frequently used as a primary endpoint in HIV clinical trials. Non-linear mixed-effects models are thus proposed to model this decrease of the viral load after initiation of treatment and to evaluate the intra-and inter-patient variability. However, left censoring due to quantification limits in the viral load measurement is an additional challenge in the analysis of longitudinal HIV data. An extension of the Stochastic Approximation Expectation-Maximization (SAEM)
doi:10.1016/j.csda.2006.05.007
fatcat:s7djufrqvncwvjmpbxe2aqogom