Double Robust Estimation

Double Robust Estimation is a semiparametric estimation method that combines models for both the outcome and the treatment assignment mechanism such that the estimator remains consistent if either model is correctly specified, but not necessarily both.

97

Publications

7.3K

Citations

188

Authors

122

Institutions

Publications per year

2017–2026

43

Variants

Doubly Robust Estimation

Authors

188

  1. MJ
    Mark J. van der Laan

    University of California, Berkeley, United States

    13 publications · 774 citations

    13

    h-index

  2. SV
    Stijn Vansteelandt

    Ghent University, Belgium

    6 publications · 179 citations

    6

    h-index

  3. SG
    Susan Gruber

    Harvard University, United States

    5 publications · 393 citations

    5

    h-index

  4. JM
    James M. Robins

    Harvard University, United States

    4 publications · 627 citations

    4

    h-index

  5. AR
    Andrea Rotnitzky

    Harvard University, United States

    4 publications · 654 citations

    4

    h-index

1–5 of 188

Venues

  1. Biometrika

    7 publications · 891 citations

    7

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  2. Biometrics

    7 publications · 170 citations

    7

    h-index

  3. The International Journal of Biostatistics

    6 publications · 837 citations

    6

    h-index

  4. Statistical Science

    6 publications · 872 citations

    6

    h-index

  5. arXiv (Cornell University)

    Repository · 5 publications · 90 citations

    5

    h-index

1–5