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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Simultaneous inference for semiparametric mixed-effects joint models with skew distribution and covariate measurement
1a Department of Mathematics and Statistics , University of Nevada , Reno , Nevada , USA.
Abstract:
Semiparametric mixed-effects joint models are flexible for modeling complex longitudinal-competing risks data. Skew distributions are commonly observed for this type of data. Covariates in the joint models are usually measured with substantial errors. We propose a Bayesian method for semiparametric mixed-effects joint models with covariate measurement errors and skew distribution. The methods are illustrated with AIDS clinical data. Simulation results are conducted to validate the proposed methods.
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