Censored linear regression models for irregularly observed longitudinal data using the multivariate-t distribution

Resumo:  In 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, in this research, 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. The methodology is illustrated through an application to a Human Immunodeficiency Virus-AIDS (HIV-AIDS). 

Local : Sala 12 do IME.

Minicurrículo: O Prof. Aldo M. Garay possui graduação em Estadística - Universidad Nacional Mayor de San Marcos (Lima, Perú), Mestrado em Estatística pelo IMECC-UNICAMP e Doutorado em Estatística pelo IME-USP. Atualmente é professor adjunto no Departamento de Estatística da Universidade Federal de Pernambuco (UFPE), atuando principalmente em áreas relacionadas a Modelos de Regressão Linear e Não Linear  Censurados, Modelos Assimétricos e Inferência Bayesiana."