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Paper   IPM / Biological Sciences / 13693
School of Biological Sciences
  Title:   A Copula Approach to Joint Modeling of Longitudinal Measurements and Survival Times Using MCEM with Application to AIDS Studies
  Author(s): 
1.  M. Ganjali.
2.  T. Baghfalaki.
  Status:   Published
  Journal: Biopharmaceutical Statistics
  No.:  5
  Vol.:  25
  Year:  2015
  Pages:   1077-1099
  Supported by:  IPM
  Abstract:
Joint modeling of longitudinal measurements and time to event data is often performed by fitting a shared parameter model. Another method for joint modeling that may be used is a marginal model. As a marginal model, we use a Gaussian model for joint modeling of longitudinal measurements and time to event data. We consider a regression model for longitudinal data modeling and a Weibull proportional hazard model for event time data modeling. A Gaussian copula is used to consider the association between these two models. A Monte Carlo expectation-maximization approach is used for parameter estimation. Some simulation studies are conducted in order to illustrate the proposed method. Also, the proposed method is used for analyzing a clinical trial dataset.

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