Joint modelling of longitudinal and time-to-event data: an overview

By Anastasios A. Tsiatis, Marie Davidian. 2004

448 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/27805687a3da0c044936bc8877b5e8249f28f27c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Dimitris Rizopoulos
2. Geert Verbeke
3. Emmanuel Lesaffre
4. Atanu Bhattacharjee
5. Geert Molenberghs
6. Hossein Soleimani
7. Cécile Proust-Lima
8. Brooke E. Magnus

Citations in the corpus

• Fully exponential Laplace approximations for the joint modelling of survival and longitudinal data (2009, background): “Shared parameter models (Tsiatis and Davidian, 2004; Follman and Wu, 1995) provide an appealing framework for the joint modelling of survival and longitudinal data.”
• Longitudinal Data Analysis (2020, background): “For example, in the cancer study example, the potential differential effects of the two causes of missingness on future responses are accommodated by adding a survival model to relate bi as a predictor to the outcome of time of death (Tsiatis and Davidian 2004).”
• Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time‐to‐Event Data (2011, methodology): “Nice overviews of this field are given by Tsiatis and Davidian (2004) and Yu et al. (2004).”