Multi-facet Generalizability Study

A Multi-Facet Generalizability Study is a type of measurement study within generalizability theory that systematically examines the relative contributions of multiple sources of variation—such as persons, raters, occasions, and items—to the overall variance in observed scores, in order to assess the dependability of measurements across diverse facets.

9

Publications

428

Citations

31

Authors

13

Institutions

Publications per year

2017–2026

2

Authors

31

  1. JA
    J. Arthur Woodward

    University of California, Los Angeles, United States

    1 publications · 31 citations

    1

    h-index

  2. CC
    Cynthia C. Gadbury‐Amyot

    University of Missouri–Kansas City, United States

    1 publications · 45 citations

    1

    h-index

  3. SY
    So Yoon Kim

    Boston College, United States

    1 publications · 12 citations

    1

    h-index

  4. HH
    Hyeri Hong

    University of Iowa, United States

    1 publications · 15 citations

    1

    h-index

  5. AE
    Ashley E. Augustine

    Vanderbilt University, United States

    1 publications · 12 citations

    1

    h-index

1–5 of 31

Venues

  1. Reading Research and Instruction

    RRI · 1 publications · 16 citations

    1

    h-index

  2. Autism Research

    1 publications · 12 citations

    1

    h-index

  3. Psych

    1 publications · 15 citations

    1

    h-index

  4. BMC Medical Education

    1 publications · 22 citations

    1

    h-index

  5. Educational and Psychological Measurement

    1 publications · 14 citations

    1

    h-index

1–5