Longitudinal Causal Inference

Longitudinal Causal Inference is a subfield of causal inference that develops theories and methods for identifying and estimating causal effects in settings with longitudinal data, where treatments, covariates, and outcomes evolve over time and may involve time-varying confounding and dynamic treatment regimes.

847

Publications

73K

Citations

2.1K

Authors

899

Institutions

Publications per year

2017–2026

332

Authors

2.1K

  1. MJ
    Mark J. van der Laan

    University of California, Berkeley, United States

    19 publications · 1.1K citations

    15

    h-index

  2. JM
    James M. Robins

    Harvard University, United States

    12 publications · 2.2K citations

    11

    h-index

  3. MA
    Miguel A. Hernán

    Harvard University, United States

    10 publications · 985 citations

    10

    h-index

  4. TJ
    Tyler J. VanderWeele

    Harvard University, United States

    9 publications · 1.4K citations

    9

    h-index

  5. RN
    Romain Neugebauer

    Kaiser Permanente, United States

    8 publications · 217 citations

    8

    h-index

1–5 of 2.1K

Venues

  1. SSRN Electronic Journal

    Repository · 47 publications · 1.5K citations

    23

    h-index

  2. Statistics in Medicine

    29 publications · 1.6K citations

    19

    h-index

  3. Journal of the American Statistical Association

    21 publications · 1.6K citations

    18

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 21 publications · 1.4K citations

    17

    h-index

  5. American Journal of Epidemiology

    AJE · 16 publications · 1.3K citations

    15

    h-index

1–5