Brasil | Artículos de revistas

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution

dc.creatorGaray
dc.creatorAldo M.; Castro
dc.creatorLuis M.; Leskow
dc.creatorJacek; Lachos
dc.creatorVictor H.
dc.date2017
dc.dateabr
dc.date2017-11-13T13:12:49Z
dc.date2017-11-13T13:12:49Z
dc.date.accessioned2018-03-29T05:50:56Z
dc.date.available2018-03-29T05:50:56Z
dc.identifierStatistical Methods In Medical Research. Sage Publications Ltd, v. 26, p. 542 - 566, 2017.
dc.identifier0962-2802
dc.identifier1477-0334
dc.identifierWOS:000399704500002
dc.identifier10.1177/0962280214551191
dc.identifierhttp://journals.sagepub.com/doi/abs/10.1177/0962280214551191
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/326940
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1363965
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionIn acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.
dc.description26
dc.description2
dc.description542
dc.description566
dc.descriptionConselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq-Brazil)
dc.descriptionFundacao de Amparo a Pesquisa do Estado de Sao Paulo from FAPESP-Brazil [2013/21468-0, 2014/02938-9]
dc.descriptionGrant FONDECYT from the Chilean government [1130233]
dc.descriptionFAPESP-Brazil [2012/19445-0, 2014/11831-3]
dc.descriptionPolish National Center for Science [UMO-2013/10/M/ST1/00096]
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.languageEnglish
dc.publisherSage Publications Ltd
dc.publisherLondon
dc.relationStatistical Methods in Medical Research
dc.rightsfechado
dc.sourceWOS
dc.subjectCensored Data
dc.subjectExpectation Conditional Maximization Algorithm
dc.subjectLongitudinal Data
dc.subjectHiv Viral Load
dc.subjectOutliers
dc.titleCensored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution
dc.typeArtículos de revistas


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