Causal Inference Under Interference

Causal Inference Under Interference is a methodological framework within causal inference that explicitly accounts for spillover effects by relaxing the assumption of non-interference, thereby allowing the causal effect of a treatment on an individual to depend on the treatment status of others.

37

Publications

3.1K

Citations

67

Authors

50

Institutions

Publications per year

2017–2026

22

Variants

Causal Inference With Interference

Authors

67

  1. MG
    Michael G. Hudgens

    University of North Carolina at Chapel Hill, United States

    5 publications · 1.1K citations

    5

    h-index

  2. EJ
    Eric J. Tchetgen Tchetgen

    Harvard University, United States

    4 publications · 523 citations

    4

    h-index

  3. SL
    Shuangning Li

    Stanford University, United States

    3 publications · 76 citations

    3

    h-index

  4. MF
    Mark Fredrickson

    University of Illinois Urbana-Champaign, United States

    3 publications · 151 citations

    3

    h-index

  5. SW
    Stefan Wager

    Stanford University, United States

    3 publications · 76 citations

    3

    h-index

1–5 of 67

Venues

  1. Journal of the American Statistical Association

    5 publications · 1.5K citations

    5

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 33 citations

    3

    h-index

  3. Biometrika

    3 publications · 139 citations

    3

    h-index

  4. arXiv (Cornell University)

    Repository · 3 publications · 50 citations

    3

    h-index

  5. The Annals of Applied Statistics

    AOAS · 2 publications · 48 citations

    2

    h-index

1–5