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---+++ Department of Biostatistics Seminar/Workshop Series ---+ <a name="Gamma_Frailty_Transformation"></a> Gamma Frailty Transformation Models for Multivariate Survival Times ---++ <a name="Qingxia_Cindy_Chen_PhD"></a> Qingxia "Cindy" Chen, !PhD ---+++ <a name="Assistant_Professor_Department"></a> Assistant Professor, Department of Biostatistics, Vanderbilt University School of Medicine ---+++ <a name="Wednesday_December_9_1_30_2_30p"></a> Wednesday, December 9, 1:30-2:30pm, MRBIII Conference Room 1220 ---+++ <a name="Intended_Audience_Persons_intere"></a> Intended Audience: Persons interested in applied statistics, statistical theory, epidemiology, health services research, clinical trials methodology, statistical computing, statistical graphics, R users or potential users We propose a class of transformation models for multivariate failure times. The class of transformation models generalize the usual gamma-frailty model and yields a marginally linear transformation model for each failure time. Nonparametric maximum likelihood estimation is used for inference. The maximum likelihood estimators for the regression coefficients are shown to be consistent and asymptotically normal, and their asymptotic variances attain the semiparametric efficiency bound. Simulation studies show that the proposed estimation procedure provides asymptotically efficient estimates and yields good inferential properties for small sample sizes. The method is illustrated using real data from a cardiovascular study.<font size="2"> </font>
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Topic revision: r2 - 26 Apr 2013,
JohnBock
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