Assessing importance of biomarkers: A Bayesian joint modelling approach of longitudinal and survival data with semi-competing risks

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Bayesian model assessment for jointly modeling multidimensional response data with application to computerized testing

Cites Work

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A general joint model for longitudinal measurements and competing risks survival data with heterogeneous random effects
Generating random correlation matrices based on vines and extended onion method
Assessing the association between trends in a biomarker and risk of event with an application in pediatric HIV/AIDS
A new joint model for longitudinal and survival data with a cure fraction
Monte Carlo methods in Bayesian computation
Estimation of treatment effects and model diagnostics with two-way time-varying treatment switching: an application to a head and neck study
Missing responses in generalised linear mixed models when the missing data mechanism is nonignorable
Joint Models for Longitudinal and Time-to-Event Data
The Evaluation of Multiple Surrogate Endpoints
Bayesian Approaches to Joint Cure-Rate and Longitudinal Models with Applications to Cancer Vaccine Trials
Modeling Disease Market Processes in AIDS
Joint Analysis of Longitudinal Data Comprising Repeated Measures and Times to Events
A Joint Model for Longitudinal Measurements and Survival Data in the Presence of Multiple Failure Types
Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach
Score Test for Conditional Independence Between Longitudinal Outcome and Time to Event Given the Classes in the Joint Latent Class Model
A Predictive Approach to Model Selection
A New Bayesian Model for Survival Data with a Surviving Fraction
Bayesian Measures of Model Complexity and Fit
Modelling Progression of CD4-Lymphocyte Count and Its Relationship to Survival Time
Joint Models for Multivariate Longitudinal and Multivariate Survival Data
The joint modeling of a longitudinal disease progression marker and the failure time process in the presence of cure
A Flexible B‐Spline Model for Multiple Longitudinal Biomarkers and Survival