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Pre-Publicación 2015-37

Luis M. Castro, Víctor H. Lachos, Larissa A. Matos:

Censored mixed-effects models for irregularly observed repeated measures with applications to HIV viral loads

Abstract:

In some AIDS clinical trials, the HIV-1 RNA measurements are collected irregularly over time and are often subject to some upper and lower detection limits, depending on the quantification assays. Linear and nonlinear mixed-effects models, with modifications to accommodate censored observations, are routinely used to analyze this type of data (Vaida and Liu, 2009; Matos et al, 2013a). The paper presents a framework for fitting LMEC/NLMEC with response variables recorded at irregular intervals. To address the serial correlation among the within-subject errors, a damped exponential correlation structure is considered in the random error and an EM-type algorithm is developed for computing the maximum likelihood estimates, obtaining as a byproduct the standard errors of the fixed effects and the likelihood value. The proposed methods are illustrated with simulations and the analysis of two real AIDS case studies.

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Esta prepublicacion dio origen a la(s) siguiente(s) publicación(es) definitiva(s):

Luis M. CASTRO, Víctor H. LACHOS, Larissa A. MATOS: Censored mixed-effects models for irregularly observed repeated measures with applications to HIV viral loads. Test, vol. 25, 4, pp. 627-653, (2016).