Censored Mixed-effects Models For Irregularly Observed Repeated Measures With Applications To Hiv Viral Loads

dc.creatorMatos
dc.creatorLarissa A.; Castro
dc.creatorLuis M.; Lachos
dc.creatorVictor H.
dc.date2016
dc.datedez
dc.date2017-11-13T13:15:21Z
dc.date2017-11-13T13:15:21Z
dc.date.accessioned2018-03-29T05:52:54Z
dc.date.available2018-03-29T05:52:54Z
dc.identifierTest. Springer, v. 25, p. 627 - 653, 2016.
dc.identifier1133-0686
dc.identifier1863-8260
dc.identifierWOS:000385139400003
dc.identifier10.1007/s11749-016-0486-2
dc.identifierhttps://link.springer.com/article/10.1007%2Fs11749-016-0486-2
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/327340
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1364365
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionIn 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.
dc.description25
dc.description4
dc.description627
dc.description653
dc.descriptionFAPESP-Brazil [2011/22063-9, 2014/02938-9]
dc.descriptionCONICYT-Chile through BASAL project CMM
dc.descriptionUniversidad de Chile
dc.descriptionChilean government [FONDECYT 1130233]
dc.descriptionCNPq-Brazil [305054/2011-2]
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.languageEnglish
dc.publisherSpringer
dc.publisherNew York
dc.relationTest
dc.rightsfechado
dc.sourceWOS
dc.subjectCensored Data
dc.subjectEm Algorithm
dc.subjectHiv Viral Load
dc.subjectIrregularly Observed Data
dc.subjectLinear/nonlinear Mixed Models
dc.titleCensored Mixed-effects Models For Irregularly Observed Repeated Measures With Applications To Hiv Viral Loads
dc.typeArtículos de revistas


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