A modified two-stage approach for joint modelling of longitudinal and time-to-event data
From MaRDI portal
Publication:4960769
DOI10.1080/00949655.2018.1518449OpenAlexW2891355402WikidataQ129272469 ScholiaQ129272469MaRDI QIDQ4960769
No author found.
Publication date: 23 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2018.1518449
Related Items (2)
Jointly modelling multiple transplant outcomes by a competing risk model via functional principal component analysis ⋮ Two-stage joint model for multivariate longitudinal and multistate processes, with application to renal transplantation data
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Random-Effects Models for Longitudinal Data
- Fast fitting of joint models for longitudinal and event time data using a pseudo-adaptive Gaussian quadrature rule
- Joint Models for Longitudinal and Time-to-Event Data
- On Estimating the Relationship between Longitudinal Measurements and Time-to-Event Data Using a Simple Two-Stage Procedure
- Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture
- Semiparametric Modeling of Longitudinal Measurements and Time‐to‐Event Data–A Two‐Stage Regression Calibration Approach
- Newton-Raphson and EM Algorithms for Linear Mixed-Effects Models for Repeated-Measures Data
- Partial likelihood
- Penalized spline joint models for longitudinal and time-to-event data
- Evaluating Surrogate Markers of Clinical Outcome When Measured with Error
- Modeling the Relationship of Survival to Longitudinal Data Measured with Error. Applications to Survival and CD4 Counts in Patients with AIDS
- Joint modelling of longitudinal measurements and event time data
This page was built for publication: A modified two-stage approach for joint modelling of longitudinal and time-to-event data