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

作     者：Matos, Larissa A. Castro, Luis M. Lachos, Victor H. 

作者机构：Univ Estadual Campinas Dept Estat Cidade Univ Zeferino Vaz Sao Paulo Brazil Univ Concepcion Dept Stat Concepcion Chile Univ Concepcion CI2MA Concepcion Chile 

出 版 物：《TEST》 (验算：西班牙统计与运筹学会杂志)

年 卷 期：2016年第25卷第4期

页      面：627-653页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 

基　　金：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] Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [11/22063-9, 14/02938-9] Funding Source: FAPESP 

主　　题：Censored data EM algorithm HIV viral load Irregularly observed data Linear/nonlinear mixed models 

摘      要：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.