Matching Methods

Matching Methods is a statistical technique in causal inference that belongs to the class of adjustment methods for observational data, distinguished by its strategy of creating comparable treatment and control groups through pairing or grouping units based on similarity in observed covariates.

2.3K

Publications

323.8K

Citations

4.7K

Authors

1.7K

Institutions

Publications per year

2017–2026

498

Authors

4.7K

  1. DB
    Donald B. Rubin

    Harvard University, United States

    32 publications · 50.1K citations

    29

    h-index

  2. EA
    Elizabeth A. Stuart

    Johns Hopkins University, United States

    28 publications · 13.1K citations

    25

    h-index

  3. PC
    Peter C. Austin

    University of Toronto, Canada

    28 publications · 30.2K citations

    24

    h-index

  4. PR
    Paul R. Rosenbaum

    University of Pennsylvania, United States

    30 publications · 1.9K citations

    24

    h-index

  5. PR
    Paul R. Rosenbaum

    University of Pennsylvania, United States

    20 publications · 47.7K citations

    19

    h-index

1–5 of 4.7K

Venues

  1. Statistics in Medicine

    78 publications · 24.6K citations

    44

    h-index

  2. Biometrics

    64 publications · 8.3K citations

    40

    h-index

  3. Journal of the American Statistical Association

    56 publications · 18K citations

    36

    h-index

  4. SSRN Electronic Journal

    Repository · 91 publications · 5.7K citations

    33

    h-index

  5. American Journal of Epidemiology

    AJE · 44 publications · 5.8K citations

    29

    h-index

1–5