Atıf İçin Kopyala
Dil E., KARASOY D.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, cilt.196, 2020 (SCI-Expanded)
-
Yayın Türü:
Makale / Tam Makale
-
Cilt numarası:
196
-
Basım Tarihi:
2020
-
Doi Numarası:
10.1016/j.cmpb.2020.105612
-
Dergi Adı:
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
-
Derginin Tarandığı İndeksler:
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
-
Anahtar Kelimeler:
gsem, Parametric joint modelling, Stata, Longitudinal data, Survival data, PROPORTIONAL HAZARDS, LIKELIHOOD APPROACH, SURVIVAL
-
TED Üniversitesi Adresli:
Evet
Özet
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.