A simple time-to-event model with NONMEM featuring right-censoring
- Author:
Quyen Thi TRAN
1
;
Jung-woo CHAE
;
Kyun-Seop BAE
;
Hwi-yeol YUN
Author Information
- Publication Type:Tutorial
- From:Translational and Clinical Pharmacology 2022;30(2):75-82
- CountryRepublic of Korea
- Language:English
- Abstract: In healthcare situations, time-to-event (TTE) data are common outcomes. A parametric approach is often employed to handle TTE data because it is possible to easily visualize different scenarios via simulation. Not all pharmacometricians are familiar with the use of non-linear mixed effects models (NONMEMs) to deal with TTE data. Therefore, this tutorial simply explains how to analyze TTE data using NONMEM. We show how to write the code and evaluate the model. We also provide an example of a hands-on model for training.
