gsem: A Stata command for parametric joint modelling of longitudinal and accelerated failure time models
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, vol.196, 2020 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 196
- Publication Date: 2020
- Doi Number: 10.1016/j.cmpb.2020.105612
- Journal Name: COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, PASCAL, Applied Science & Technology Source, BIOSIS, Biotechnology Research Abstracts, Compendex, Computer & Applied Sciences, EMBASE, INSPEC, MEDLINE
- Hacettepe University Affiliated: Yes
Abstract
Background: The number of studies using joint modelling of longitudinal and survival data have increased in the past two decades, but analytical techniques and software shortcomings have remained. A joint model is often used for analysis of a combination of longitudinal sub-model and survival sub-model using shared random effects. Cox regression commonly referring to the survival sub-model, should not be used when proportional hazards assumptions are not satisfied. In such cases, the parametric survival model is preferable.