Selection Bias Correction

Selection Bias Correction is a methodological approach in statistical modeling that addresses systematic distortions arising from non-random sample selection by adjusting estimates to ensure valid inference under the assumption of missing-not-at-random data.

328

Publications

56.6K

Citations

791

Authors

448

Institutions

Publications per year

2017–2026

81

Authors

791

  1. DB
    Donald B. Rubin

    Harvard University, United States

    4 publications · 1.6K citations

    4

    h-index

  2. HY
    Hirokazu Yanagihara

    Hiroshima University, Japan

    4 publications · 64 citations

    4

    h-index

  3. BM
    Bhramar Mukherjee

    University of Michigan, United States

    4 publications · 148 citations

    4

    h-index

  4. HW
    Howard Wainer

    Educational Testing Service, United States

    3 publications · 74 citations

    3

    h-index

  5. FB
    Françoìs Bourguignon

    Paris School of Economics, France

    3 publications · 178 citations

    3

    h-index

1–5 of 791

Venues

  1. SSRN Electronic Journal

    Repository · 15 publications · 1.1K citations

    14

    h-index

  2. Journal of the American Statistical Association

    10 publications · 1.7K citations

    10

    h-index

  3. RePEc: Research Papers in Economics

    Repository · 8 publications · 443 citations

    8

    h-index

  4. Journal of Econometrics

    6 publications · 693 citations

    6

    h-index

  5. Biometrics

    6 publications · 1.5K citations

    6

    h-index

1–5