Spline-based Survival Models

Spline-Based Survival Models is a statistical modeling framework within survival analysis that uses spline functions to flexibly model the time-varying effects of covariates or the baseline hazard function, thereby enabling more accurate and smooth estimations of survival probabilities compared to traditional parametric or piecewise approaches.

149

Publications

13K

Citations

656

Authors

351

Institutions

Publications per year

2017–2026

54

Authors

656

  1. PC
    Paul C. Lambert

    University of Leicester, United Kingdom

    9 publications · 941 citations

    9

    h-index

  2. MJ
    Michael J. Crowther

    University of Leicester, United Kingdom

    6 publications · 405 citations

    6

    h-index

  3. MA
    Michał Abrahamowicz

    McGill University, Canada

    6 publications · 305 citations

    6

    h-index

  4. CK
    Charles Kooperberg

    Fred Hutch Cancer Center, United States

    4 publications · 356 citations

    4

    h-index

  5. NB
    Nadine Bossard

    Hospices Civils de Lyon, France

    3 publications · 112 citations

    3

    h-index

1–5 of 656

Venues

  1. Statistics in Medicine

    22 publications · 5.8K citations

    19

    h-index

  2. Biometrics

    12 publications · 1K citations

    12

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 5 publications · 175 citations

    5

    h-index

  4. Statistical Methods in Medical Research

    4 publications · 98 citations

    4

    h-index

  5. 3

    h-index

1–5