Assumption Checking

Assumption Checking is the systematic evaluation of the validity of presupposed conditions underlying a statistical model, particularly in Random-Effects Models, to ensure that the theoretical requirements necessary for unbiased and efficient estimation are empirically tenable.

152

Publications

12.9K

Citations

332

Authors

193

Institutions

Publications per year

2017–2026

27

Authors

332

  1. HJ
    H. J. Keselman

    University of Manitoba, Canada

    5 publications · 820 citations

    5

    h-index

  2. GV
    Gene V. Glass

    University of Colorado System, United States

    3 publications · 1.9K citations

    3

    h-index

  3. SF
    Sandra Ferketich

    University of Arizona, United States

    3 publications · 105 citations

    3

    h-index

  4. JA
    Joyce A. Verran

    University of Arizona, United States

    3 publications · 105 citations

    3

    h-index

  5. LM
    Lisa M. Lix

    University of Manitoba, Canada

    3 publications · 691 citations

    3

    h-index

1–5 of 332

Venues

  1. The American Statistician

    7 publications · 334 citations

    7

    h-index

  2. Review of Educational Research

    RER · 6 publications · 2.6K citations

    6

    h-index

  3. Computational Statistics & Data Analysis

    CSDA · 5 publications · 506 citations

    5

    h-index

  4. Statistics in Medicine

    3 publications · 160 citations

    3

    h-index

  5. arXiv (Cornell University)

    Repository · 3 publications · 72 citations

    3

    h-index

1–5