Continuous-time Survival Models

Continuous-Time Survival Models is a statistical modeling framework that belongs to the class of survival analysis methods, distinguished by its specification of the hazard function as a continuous function of time, enabling the estimation of event occurrence probabilities at any instant without discretization of the time scale.

299

Publications

24.1K

Citations

903

Authors

458

Institutions

Publications per year

2017–2026

65

Authors

903

  1. TK
    Thomas Kneib

    University of Göttingen, Germany

    5 publications · 228 citations

    5

    h-index

  2. CT
    Chap T. Le

    University of Minnesota, United States

    4 publications · 465 citations

    4

    h-index

  3. PM
    Patricia M. Grambsch

    University of Minnesota, United States

    3 publications · 1.2K citations

    3

    h-index

  4. TE
    Tim Eakin

    Balcones Technologies (United States), United States

    2 publications · 26 citations

    2

    h-index

  5. DE
    Douglas E. Schaubel

    University of Michigan, United States

    2 publications · 48 citations

    2

    h-index

1–5 of 903

Venues

  1. Biometrics

    15 publications · 3.7K citations

    14

    h-index

  2. Statistics in Medicine

    14 publications · 766 citations

    12

    h-index

  3. PubMed

    Repository · 15 publications · 570 citations

    12

    h-index

  4. Lifetime Data Analysis

    6 publications · 237 citations

    6

    h-index

  5. Technometrics

    6 publications · 2.9K citations

    6

    h-index

1–5