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--></style></head><body lang=IT link=blue vlink=purple><div class=WordSection1><p><span style='font-size:10.0pt;font-family:"Verdana",sans-serif'>*************************************<o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Seminario di Statistica<o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Dipartimento di Scienze Economiche e Statistiche - <span style='color:#1F497D'><a href="http://www.dises.unisa.it/">DiSES</a></span> <o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><b><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Università degli Studi di Salerno</span></b><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'><o:p></o:p></span></p><p><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>*************************************<o:p></o:p></span></p><p><strong><span style='font-size:16.0pt;font-family:"Tahoma",sans-serif'>Marcella Mazzoleni -</span></strong><strong><span style='font-size:16.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'> Università di Milano Bicocca<o:p></o:p></span></strong></p><p><strong><i><span style='font-size:16.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>"Joint models for time-to-event and multivariate longitudinal data: a likelihood approach"<o:p></o:p></span></i></strong></p><p><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>15 Maggio 2018, h. 15.00 - Sala dei Consigli DISES<o:p></o:p></span></strong></p><p><strong><i><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>Abstract<o:p></o:p></span></i></strong></p><p><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>The joint models analyse the effect of longitudinal covariates onto the risk of one or more events. They are composed of two sub-models, the longitudinal and the survival sub-model. For the longitudinal sub-model a multivariate mixed model is used, considering fixed and random effects. Whereas for the survival sub-model, a Cox proportional hazards model is proposed, considering jointly the influence of more than one longitudinal covariate onto the risk of the event. The purpose of the presentation is to show the extension of a univariate estimation method based on a joint likelihood formulation to the case in which the longitudinal sub-model is multivariate. The estimation method is based on the maximisation of the likelihood function achieved through the implementation of an Expectation-Maximisation (EM) algorithm. In the M-step a one-step Newton-Raphson update is used, as for some parameters estimators, it is not possible to obtain closed-form expression. In addition, a Gauss-Hermite approximation is applied for some of the integrals involved. Some simulation results and an application to a well-known dataset are shown.<o:p></o:p></span></strong></p><p><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>This is a joint work with: </span></strong><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Mariangela Zenga</span></strong><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>.<o:p></o:p></span></strong></p><p><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'><o:p> </o:p></span></strong></p><p><strong><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif;font-weight:normal'>Laboratorio di Ricerca e Formazione avanzata in Statistica</span></strong><b><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'> </span></b><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'><a href="http://www.statlab.unisa.it/index">STATLAB</a><o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Università degli Studi di Salerno<o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Via Giovanni Paolo II, 132<o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>84084 Fisciano SA<o:p></o:p></span></p><p style='margin:0cm;margin-bottom:.0001pt'><span style='font-size:14.0pt;font-family:"Tahoma",sans-serif'>Tel. +39 089 96 3132<o:p></o:p></span></p><p style='margin-bottom:12.0pt'><span lang=EN-US style='font-size:14.0pt;font-family:"Tahoma",sans-serif'><o:p> </o:p></span></p><p><span lang=EN-US style='font-family:"Tahoma",sans-serif'><o:p> </o:p></span></p></div></body></html>