Parametric Regression Models

Parametric Regression Models is a type of survival regression model that assumes a specific mathematical form for the baseline hazard function, distinguishing it from nonparametric and semiparametric models by requiring full specification of the distributional parameters governing event times.

1.3K

Publications

124.6K

Citations

3.3K

Authors

1.3K

Institutions

Publications per year

2017–2026

316

Authors

3.3K

  1. DY
    D. Y. Lin

    University of North Carolina at Chapel Hill, United States

    11 publications · 1.6K citations

    11

    h-index

  2. MA
    Michał Abrahamowicz

    McGill University, Canada

    9 publications · 302 citations

    9

    h-index

  3. LJ
    L. J. Wei

    Harvard University, United States

    8 publications · 2K citations

    8

    h-index

  4. JF
    Jianqing Fan

    Princeton University, United States

    8 publications · 10.8K citations

    8

    h-index

  5. IV
    Ingrid Van Keilegom

    UCLouvain, Belgium

    8 publications · 194 citations

    8

    h-index

1–5 of 3.3K

Venues

  1. Journal of the American Statistical Association

    72 publications · 23.2K citations

    45

    h-index

  2. Biometrics

    49 publications · 4.7K citations

    35

    h-index

  3. Statistics in Medicine

    68 publications · 6.6K citations

    31

    h-index

  4. Biometrika

    30 publications · 3.9K citations

    25

    h-index

  5. 24

    h-index

1–5