Alternative Adjustment Sets

Alternative Adjustment Sets is a methodological construct in causal inference that identifies distinct subsets of covariates satisfying adjustment criteria for unbiased effect estimation, differing in composition while maintaining equivalent statistical and causal validity under a given graphical model.

12

Publications

2.7K

Citations

34

Authors

20

Institutions

Publications per year

2017–2026

3

Authors

34

  1. ML
    Maciej Liśkiewicz

    University of Lübeck, Germany

    2 publications · 2.3K citations

    2

    h-index

  2. BV
    Benito van der Zander

    University of Lübeck, Germany

    2 publications · 2.3K citations

    2

    h-index

  3. JT
    Johannes Textor

    Radboud University Nijmegen, Netherlands

    2 publications · 2.3K citations

    2

    h-index

  4. NÖ
    Nadir Öcal

    Middle East Technical University, Türkiye

    1 publications · 14 citations

    1

    h-index

  5. EJ
    E. J. Pollak

    Cornell University, United States

    1 publications · 10 citations

    1

    h-index

1–5 of 34

Venues

  1. Journal of Animal Science

    2 publications · 20 citations

    2

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  2. American Journal of Epidemiology

    AJE · 1 publications · 29 citations

    1

    h-index

  3. International Conference on Artificial Intelligence and Statistics

    Conference · 1 publications · 37 citations

    1

    h-index

  4. Artificial Intelligence

    1 publications · 34 citations

    1

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  5. Regional Studies

    1 publications · 122 citations

    1

    h-index

1–5