G-formula

G-Formula is a mathematical method in causal inference that, within longitudinal settings, identifies the causal effect of time-varying treatments by adjusting for time-dependent confounders through sequential conditional expectation under a specified causal model.

98

Publications

5.6K

Citations

422

Authors

264

Institutions

Publications per year

2017–2026

63

Variants

G-computationG-computation Algorithm

Authors

422

  1. MA
    Miguel A. Hernán

    Harvard University, United States

    22 publications · 1.6K citations

    18

    h-index

  2. JM
    James M. Robins

    Harvard University, United States

    14 publications · 1.2K citations

    13

    h-index

  3. JG
    Jessica G. Young

    Harvard University, United States

    11 publications · 864 citations

    11

    h-index

  4. RL
    Roger Logan

    Harvard University, United States

    8 publications · 358 citations

    8

    h-index

  5. SR
    Stephen R. Cole

    University of North Carolina at Chapel Hill, United States

    8 publications · 522 citations

    8

    h-index

1–5 of 422

Venues

  1. Epidemiology

    10 publications · 521 citations

    9

    h-index

  2. American Journal of Epidemiology

    AJE · 7 publications · 409 citations

    7

    h-index

  3. Statistics in Medicine

    7 publications · 449 citations

    7

    h-index

  4. International Journal of Epidemiology

    4 publications · 496 citations

    4

    h-index

  5. arXiv (Cornell University)

    Repository · 4 publications · 96 citations

    4

    h-index

1–5