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JMFit: A SAS Macro for Joint Models of Longitudinal and Survival Data.
Zhang, Danjie; Chen, Ming-Hui; Ibrahim, Joseph G; Boye, Mark E; Shen, Wei.
Afiliación
  • Zhang D; Gilead Sciences, Inc., 333 Lakeside Drive, Foster City, CA 94404, U.S.A., danjie.zhang@gilead.com.
  • Chen MH; Department of Statistics, University of Connecticut, 215 Glenbrook Road U-4120, Storrs, CT 06269, U.S.A., ming-hui.chen@uconn.edu.
  • Ibrahim JG; Department of Biostatistics, University of North Carolina, McGavran Greenberg Hall CB#7420, Chapel Hill, NC 27599, U.S.A., ibrahim@bios.unc.edu.
  • Boye ME; Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, U.S.A., boyema@lilly.com.
  • Shen W; Eli Lilly and Company, Lilly Corporate Center, Indianapolis, IN 46285, U.S.A., shen_wei_x1@lilly.com.
J Stat Softw ; 71(3)2016 Jul.
Article en En | MEDLINE | ID: mdl-27616941
ABSTRACT
Joint models for longitudinal and survival data now have a long history of being used in clinical trials or other studies in which the goal is to assess a treatment effect while accounting for a longitudinal biomarker such as patient-reported outcomes or immune responses. Although software has been developed for fitting the joint model, no software packages are currently available for simultaneously fitting the joint model and assessing the fit of the longitudinal component and the survival component of the model separately as well as the contribution of the longitudinal data to the fit of the survival model. To fulfill this need, we develop a SAS macro, called JMFit. JMFit implements a variety of popular joint models and provides several model assessment measures including the decomposition of AIC and BIC as well as ΔAIC and ΔBIC recently developed in Zhang et al. (2014). Examples with real and simulated data are provided to illustrate the use of JMFit.
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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Stat Softw Año: 2016 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: J Stat Softw Año: 2016 Tipo del documento: Article