Artículos de revistas
Censored Mixed-effects Models For Irregularly Observed Repeated Measures With Applications To Hiv Viral Loads
Registro en:
Test. Springer, v. 25, p. 627 - 653, 2016.
1133-0686
1863-8260
WOS:000385139400003
10.1007/s11749-016-0486-2
Autor
Matos
Larissa A.; Castro
Luis M.; Lachos
Victor H.
Institución
Resumen
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) In some acquired immunodeficiency syndrome (AIDS) clinical trials, the human immunodeficiency virus-1 ribonucleic acid 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, J Comput Graph Stat 18:797-817, 2009; Matos et al., Comput Stat Data Anal 57(1):450-464, 2013a). This 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. 25 4 627 653 FAPESP-Brazil [2011/22063-9, 2014/02938-9] CONICYT-Chile through BASAL project CMM Universidad de Chile Chilean government [FONDECYT 1130233] CNPq-Brazil [305054/2011-2] Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)