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Recent Posts
Recent Publications
An alternative characterization of Missing at Random in Shared Parameter Models for incomplete longitudinal data and its utilization for sensitivity analysis
Pairwise estimation of multivariate longitudinal outcomes in a Bayesian setting with extensions to the joint model
A Bayesian joint model for zero-inflated integers and left-truncated event times with a time-varying association: Applications to senior health care
A marginal estimate for the overall treatment effect on a survival outcome within the joint modeling framework
Joint modeling of longitudinal continuous, longitudinal ordinal, and time-to-event outcomes
Integrating latent classes in the Bayesian shared parameter joint model of longitudinal and survival outcomes
Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach
Personalized decision making for biopsies in prostate cancer active surveillance programs
Bayesian imputation of time-varying covariates in linear mixed models
Joint models for longitudinal and time-to-event data in a case-cohort design
Personalized schedules for surveillance of low risk prostate cancer patients
Improved dynamic predictions from joint models of longitudinal and survival data with time-varying effects using P-splines
Approximate likelihood inference in generalized linear latent variable models based on the dimension-wise quadrature
Dynamic predictions with time-dependent covariates in survival analysis using joint modeling and landmarking
Extension of the association structure in joint models to include weighted cumulative effects
Bayesian shrinkage approach for a joint model of longitudinal and survival outcomes assuming different association structures
The R package JMbayes for fitting joint Models for longitudinal and time-to-event data using MCMC
Dealing with missing covariates in epidemiologic studies: A comparison between multiple imputation and a full Bayesian approach
Personalized screening intervals for biomarkers using joint models for longitudinal and survival data
Combining dynamic predictions from joint models for longitudinal and time-to-event data using Bayesian model averaging