Fitting joint models of longitudinal observations and time to event by sequential Bayesian updating

Joint models with multiple longitudinal outcomes and a time-to-event outcome: a corrected two-stage approach

(2020) Katya Mauff et al.   STATISTICS AND COMPUTING

Exploring causality mechanism in the joint analysis of longitudinal and survival data

(2018) Lei Liu et al.   STATISTICS IN MEDICINE

Continuous Time Structural Equation Modeling with R Package ctsem

(2017) Charles C. Driver et al.   Journal of Statistical Software

Joint modelling of time-to-event and multivariate longitudinal outcomes: recent developments and issues

(2016) Graeme L. Hickey et al.   BMC Medical Research Methodology

Joint modelling of repeated measurement and time-to-event data: an introductory tutorial

(2015) Özgür Asar et al.   INTERNATIONAL JOURNAL OF EPIDEMIOLOGY

Real-time monitoring of progression towards renal failure in primary care patients

(2014) P. J. Diggle et al.   BIOSTATISTICS

Fast Kalman Filtering and Forward–Backward Smoothing via a Low-Rank Perturbative Approach

(2013) Eftychios A. Pnevmatikakis et al.   JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS

Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture

(2011) Michael J. Sweeting et al.   BIOMETRICAL JOURNAL

Dynamic predicting by landmarking as an alternative for multi-state modeling: an application to acute lymphoid leukemia data

(2008) Hans C. van Houwelingen et al.   LIFETIME DATA ANALYSIS

Immortal Time Bias in Pharmacoepidemiology

(2007) S. Suissa   AMERICAN JOURNAL OF EPIDEMIOLOGY