Bayesian Survival Analysis

Bayesian Survival Analysis is a statistical methodology within survival analysis that employs Bayesian inference to model time-to-event data, incorporating prior distributions to estimate posterior probabilities of survival outcomes.

594

Publications

25.7K

Citations

2.8K

Authors

940

Institutions

Publications per year

2017–2026

164

Authors

2.8K

  1. JG
    Joseph G. Ibrahim

    University of North Carolina at Chapel Hill, United States

    18 publications · 1.4K citations

    15

    h-index

  2. DD
    David D. Hanagal

    Savitribai Phule Pune University, India

    15 publications · 237 citations

    11

    h-index

  3. DS
    Debajyoti Sinha

    Florida State University, United States

    10 publications · 1K citations

    10

    h-index

  4. AP
    Arvind Pandey

    Savitribai Phule Pune University, India

    9 publications · 138 citations

    9

    h-index

  5. DK
    Dipak K. Dey

    University of Connecticut, United States

    8 publications · 293 citations

    8

    h-index

1–5 of 2.8K

Venues

  1. Biometrics

    52 publications · 2.4K citations

    30

    h-index

  2. Statistics in Medicine

    55 publications · 2K citations

    26

    h-index

  3. Journal of the American Statistical Association

    15 publications · 1.7K citations

    14

    h-index

  4. Communication in Statistics- Theory and Methods

    18 publications · 478 citations

    14

    h-index

  5. Scandinavian Journal of Statistics

    11 publications · 446 citations

    11

    h-index

1–5