Facet Variance Estimation

Facet Variance Estimation is a statistical procedure in generalizability theory that quantifies the contribution of specific facets—such as persons, raters, or items—to the overall variance in observed scores, thereby distinguishing it from other variance partitioning methods by its focus on the reliability and dependability of measurements across crossed and nested facets in G-study design.

11

Publications

522

Citations

34

Authors

25

Institutions

Publications per year

2017–2026

2

Authors

34

  1. DR
    Dale R. Fuqua

    Oklahoma State University, United States

    1 publications · 11 citations

    1

    h-index

  2. BK
    Ben Kelcey

    University of Cincinnati, United States

    1 publications · 31 citations

    1

    h-index

  3. RV
    Rimas V. Lukas

    Northwestern University, United States

    1 publications · 28 citations

    1

    h-index

  4. JR
    James R. Brorson

    University of Chicago, United States

    1 publications · 28 citations

    1

    h-index

  5. SS
    Sylvia Sastre i Riba

    Universidad de La Rioja, Spain

    1 publications · 16 citations

    1

    h-index

1–5 of 34

Venues

  1. Educational and Psychological Measurement

    2 publications · 289 citations

    2

    h-index

  2. Medical Teacher

    2 publications · 41 citations

    2

    h-index

  3. Journal of Geophysical Research Atmospheres

    JGR · 1 publications · 24 citations

    1

    h-index

  4. Applied Psychological Measurement

    1 publications · 11 citations

    1

    h-index

  5. Neurology

    1 publications · 28 citations

    1

    h-index

1–5