Variance Component Interpretation

Variance Component Interpretation is a methodological framework within error variance decomposition that identifies and quantifies the contribution of distinct sources of variability in a statistical model by partitioning total variance into interpretable, additive components attributable to specific factors or levels of analysis.

64

Publications

8K

Citations

158

Authors

90

Institutions

Publications per year

2017–2026

6

Authors

158

  1. SE
    Sebastián Edwards

    University of California, Los Angeles, United States

    2 publications · 37 citations

    2

    h-index

  2. SV
    Sergey V. Beiden

    Center for Devices and Radiological Health, United States

    2 publications · 169 citations

    2

    h-index

  3. LE
    László Endrényi

    University of Toronto, Canada

    2 publications · 49 citations

    2

    h-index

  4. KE
    Kevin E. O’Grady

    University of Maryland, College Park, United States

    2 publications · 206 citations

    2

    h-index

  5. GC
    Gregory Campbell

    National Institutes of Health, United States

    2 publications · 169 citations

    2

    h-index

1–5 of 158

Venues

  1. Academic Radiology

    3 publications · 244 citations

    3

    h-index

  2. Biometrika

    2 publications · 128 citations

    2

    h-index

  3. Genetics

    2 publications · 31 citations

    2

    h-index

  4. Psychological Bulletin

    2 publications · 206 citations

    2

    h-index

  5. Strategic Management Journal

    SMJ · 2 publications · 171 citations

    2

    h-index

1–5