Random Effects Survival Models is a parametric survival model that incorporates unobserved heterogeneity by introducing random effects, typically assumed to follow a specified distribution, to account for clustering or correlation in time-to-event data.
121
Publications
7.2K
Citations
532
Authors
314
Institutions
Publications per year
2017–2026
19
Publications
121
The power prior: theory and applications
Joseph G. Ibrahim, Ming‐Hui Chen, Yeongjin Gwon et al. · Statistics in Medicine · 2015 · 353 citations
Depressive Symptoms and Cognitive Decline in Late Life
Mary Ganguli, Yangchun Du, Hiroko H. Dodge et al. · Archives of General Psychiatry · 2006 · 316 citations
Proportional hazards model with random effects
Florin Vaida, Ronghui Xu · Statistics in Medicine · 2000 · 229 citations
1–5 of 121
Authors
532
- KK
4
h-index
- VR
3
h-index
- AA
3
h-index
- KF
3
h-index
- GT
3
h-index
1–5 of 532
Institutions
314
Harvard University
Cambridge, United States
9 h-index
21 publications
1.8K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
7 h-index
11 publications
676 citations
Inserm
Paris, France
6 h-index
19 publications
465 citations
Brigham and Women's Hospital
Boston, United States
5 h-index
12 publications
699 citations
National Cancer Institute
Bethesda, United States
5 h-index
8 publications
430 citations
KU Leuven
Leuven, Belgium
4 h-index
8 publications
388 citations
City University of Hong Kong
Hong Kong, Hong Kong
4 h-index
6 publications
222 citations
Erasmus MC
Rotterdam, The Netherlands
4 h-index
10 publications
769 citations
1–8 of 314
Venues
- Statistics in Medicine
17 publications · 1.5K citations
15
h-index
- Biometrics
9 publications · 617 citations
9
h-index
- Statistical Methods in Medical Research
8 publications · 274 citations
8
h-index
- Journal of the American Statistical Association
4 publications · 292 citations
4
h-index
- Animal Conservation
3 publications · 107 citations
3
h-index
1–5