Bayesian semiparametric modeling for HIV longitudinal data with censoring and skewness

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dc.contributor.authorCastro, Luis M.
dc.contributor.authorWang, Wan-Lun
dc.contributor.authorLachos, Victor H.
dc.contributor.authorde Carvalho, Vanda Inacio
dc.contributor.authorBayes, Cristian L.
dc.date.accessioned2025-01-23T21:16:02Z
dc.date.available2025-01-23T21:16:02Z
dc.date.issued2019
dc.description.abstractIn biomedical studies, the analysis of longitudinal data based on Gaussian assumptions is common practice. Nevertheless, more often than not, the observed responses are naturally skewed, rendering the use of symmetric mixed effects models inadequate. In addition, it is also common in clinical assays that the patient's responses are subject to some upper and/or lower quantification limit, depending on the diagnostic assays used for their detection. Furthermore, responses may also often present a nonlinear relation with some covariates, such as time. To address the aforementioned three issues, we consider a Bayesian semiparametric longitudinal censored model based on a combination of splines, wavelets, and the skew-normal distribution. Specifically, we focus on the use of splines to approximate the general mean, wavelets for modeling the individual subject trajectories, and on the skew-normal distribution for modeling the random effects. The newly developed method is illustrated through simulated data and real data concerning AIDS/HIV viral loads.
dc.fuente.origenWOS
dc.identifier.doi10.1177/0962280218760360
dc.identifier.eissn1477-0334
dc.identifier.issn0962-2802
dc.identifier.urihttps://doi.org/10.1177/0962280218760360
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/101109
dc.identifier.wosidWOS:000465135000011
dc.issue.numero5
dc.language.isoen
dc.pagina.final1476
dc.pagina.inicio1457
dc.revistaStatistical methods in medical research
dc.rightsacceso restringido
dc.subjectCensored longitudinal data
dc.subjectHIV viral load
dc.subjectmixed-effects models
dc.subjectsemiparametric regression
dc.subjectskewness
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleBayesian semiparametric modeling for HIV longitudinal data with censoring and skewness
dc.typeartículo
dc.volumen28
sipa.indexWOS
sipa.trazabilidadWOS;2025-01-12
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