Confounding Adjustment

Confounding Adjustment is a statistical methodology within propensity modeling that specifically corrects for non-causal associations arising from confounding variables by estimating and accounting for the conditional probability of treatment assignment given observed covariates.

2.6K

Publications

271.8K

Citations

10.7K

Authors

3.1K

Institutions

Publications per year

2017–2026

869

Authors

10.7K

  1. TJ
    Tyler J. VanderWeele

    Harvard University, United States

    27 publications · 12.3K citations

    24

    h-index

  2. RJ
    Robert J. Glynn

    Brigham and Women's Hospital, United States

    24 publications · 4.8K citations

    21

    h-index

  3. SS
    Sebastian Schneeweiß

    Brigham and Women's Hospital, United States

    23 publications · 4.9K citations

    19

    h-index

  4. SG
    Sander Greenland

    University of California, Los Angeles, United States

    19 publications · 9.1K citations

    18

    h-index

  5. TS
    Til Stürmer‎

    University of North Carolina at Chapel Hill, United States

    19 publications · 2.9K citations

    17

    h-index

1–5 of 10.7K

Venues

  1. American Journal of Epidemiology

    AJE · 91 publications · 20.7K citations

    56

    h-index

  2. Statistics in Medicine

    78 publications · 15.6K citations

    40

    h-index

  3. Epidemiology

    48 publications · 14.2K citations

    32

    h-index

  4. PubMed

    Repository · 85 publications · 3.6K citations

    31

    h-index

  5. PLoS ONE

    49 publications · 2.8K citations

    27

    h-index

1–5