Incorporating longitudinal biomarkers for dynamic risk prediction in the era of big data: a pseudo-observation approach

Cites Work

Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule
An approach for jointly modeling multivariate longitudinal measurements and discrete time-to-event data
Pseudo-observations for competing risks with covariate dependent censoring
Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data
Standard errors for bagged and random forest estimators
Joint modelling of multivariate longitudinal outcomes and a time-to-event: a nonlinear latent class approach
Recursive partitioning and applications
Practical considerations of the jackknife estimator of variance for generalized estimating equations
Semiparametric Bayesian joint models of multivariate longitudinal and survival data
Classification of repeated measurements data using tree-based ensemble methods
Joint modeling of multivariate longitudinal mixed measurements and time to event data using a Bayesian approach
Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data
Models for Longitudinal Data: A Generalized Estimating Equation Approach
Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach
Quantifying the Predictive Performance of Prognostic Models for Censored Survival Data with Time-Dependent Covariates
Predicting renal graft failure using multivariate longitudinal profiles
Jointly Modeling Longitudinal and Event Time Data With Application to Acquired Immunodeficiency Syndrome
Random survival forests for high‐dimensional data
Consistent Estimation of the Expected Brier Score in General Survival Models with Right‐Censored Event Times
On longitudinal prediction with time‐to‐event outcome: Comparison of modeling options
Regression Analysis for Multistate Models Based on a Pseudo‐value Approach, with Applications to Bone Marrow Transplantation Studies
Dynamic Prediction by Landmarking in Event History Analysis
Identification and efficacy of longitudinal markers for survival
Survival Model Predictive Accuracy and ROC Curves
Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
Random forests