Small-sample Bias Correction

Small-Sample Bias Correction is a statistical method designed to adjust effect size estimates to reduce systematic error that arises due to limited sample sizes, thereby improving the accuracy of inferential conclusions in quantitative research.

222

Publications

23.1K

Citations

434

Authors

275

Institutions

Publications per year

2017–2026

31

Authors

434

  1. LV
    Larry V. Hedges

    University of Chicago, United States

    5 publications · 400 citations

    5

    h-index

  2. GD
    Glenn D. Rudebusch

    Federal Reserve Bank of San Francisco, United States

    3 publications · 429 citations

    3

    h-index

  3. DM
    Daniel McNeish

    Arizona State University, United States

    3 publications · 384 citations

    3

    h-index

  4. LG
    Luca Guerrieri

    Federal Reserve, United States

    3 publications · 261 citations

    3

    h-index

  5. FR
    Federico Ravenna

    University of California, Santa Cruz, United States

    3 publications · 254 citations

    3

    h-index

1–5 of 434

Venues

  1. SSRN Electronic Journal

    Repository · 17 publications · 582 citations

    13

    h-index

  2. Statistics in Medicine

    10 publications · 641 citations

    10

    h-index

  3. Journal of Business and Economic Statistics

    JBES · 5 publications · 1.3K citations

    5

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 5 publications · 1.4K citations

    5

    h-index

  5. Journal of Econometrics

    4 publications · 259 citations

    4

    h-index

1–5