Parametric G-formula

The Parametric G-Formula is a statistical method that extends the general G-formula by specifying a parametric model for the conditional distributions of time-varying treatments and confounders to estimate causal effects under time-varying interventions.

80

Publications

4.1K

Citations

406

Authors

263

Institutions

Publications per year

2017–2026

55

Variants

Parametric G-computationParametric G-formulae

Authors

406

  1. MA
    Miguel A. Hernán

    Harvard University, United States

    20 publications · 1.5K citations

    18

    h-index

  2. SR
    Stephen R. Cole

    University of North Carolina at Chapel Hill, United States

    11 publications · 721 citations

    11

    h-index

  3. JM
    James M. Robins

    Harvard University, United States

    10 publications · 894 citations

    10

    h-index

  4. JG
    Jessica G. Young

    Harvard University, United States

    10 publications · 769 citations

    10

    h-index

  5. RL
    Roger Logan

    Harvard University, United States

    8 publications · 358 citations

    8

    h-index

1–5 of 406

Venues

  1. Epidemiology

    10 publications · 554 citations

    9

    h-index

  2. American Journal of Epidemiology

    AJE · 8 publications · 475 citations

    8

    h-index

  3. Statistics in Medicine

    5 publications · 688 citations

    5

    h-index

  4. International Journal of Epidemiology

    5 publications · 548 citations

    5

    h-index

  5. 3

    h-index

1–5