Mixture Survival Models is a class of survival models that incorporates heterogeneity in time-to-event data by representing the population as a probabilistic combination of distinct subpopulations, each with its own survival distribution, thereby allowing for differential risk patterns and event dynamics across latent groups.
192
Publications
10.9K
Citations
566
Authors
343
Institutions
Publications per year
2017–2026
40
Parents
Publications
192
1–5 of 192
Authors
566
- YP
6
h-index
- RCRam C. Tiwari
United States Food and Drug Administration, United States
6 publications · 276 citations
6
h-index
- PC
6
h-index
- RD
5
h-index
- GJ
5
h-index
1–5 of 566
Institutions
343
The University of Queensland
Brisbane, Australia
6 h-index
9 publications
231 citations
University of Leicester
Leicester, United Kingdom
6 h-index
9 publications
803 citations
Karolinska Institutet
Stockholm, Sweden
6 h-index
15 publications
831 citations
Queen's University
Kingston, Canada
6 h-index
9 publications
250 citations
National Cancer Institute
Bethesda, United States
6 h-index
11 publications
334 citations
KU Leuven
Leuven, Belgium
5 h-index
11 publications
475 citations
University of South Carolina
Columbia, United States
5 h-index
5 publications
217 citations
University of the Free State
Bloemfontein, South Africa
5 h-index
5 publications
174 citations
1–8 of 343
Venues
- Statistics in Medicine
26 publications · 1.5K citations
19
h-index
- Journal of the American Statistical Association
12 publications · 2.1K citations
12
h-index
- Statistical Methods in Medical Research
9 publications · 195 citations
9
h-index
- Computational Statistics & Data Analysis
CSDA · 6 publications · 143 citations
6
h-index
- Biometrics
6 publications · 968 citations
6
h-index
1–5