Multifacet Generalizability Analysis

Multifacet Generalizability Analysis is a psychometric framework within error variance decomposition that extends generalizability theory by simultaneously accounting for multiple sources of measurement error variance arising from crossed and nested facets, such as raters, occasions, items, and domains, to assess the dependability of scores across diverse testing conditions.

6

Publications

296

Citations

10

Authors

7

Institutions

Publications per year

2017–2026

0

Authors

10

  1. KA
    Knut A. Hagtvet

    University of Oslo, Norway

    1 publications · 12 citations

    1

    h-index

  2. PD
    Peter D. MacMillan

    University of Northern British Columbia, Canada

    1 publications · 25 citations

    1

    h-index

  3. RL
    Robert L. Brennan

    University of Iowa, United States

    1 publications · 41 citations

    1

    h-index

  4. NR
    Nageswari Rajaratnam

    University of Illinois System, United States

    1 publications · 150 citations

    1

    h-index

  5. AG
    Atta Gebril

    American University in Cairo, Egypt

    1 publications · 50 citations

    1

    h-index

1–5 of 10

Venues

  1. Psychometrika

    1 publications · 150 citations

    1

    h-index

  2. Assessing Writing

    1 publications · 50 citations

    1

    h-index

  3. Applied Psychological Measurement

    1 publications · 41 citations

    1

    h-index

  4. Educational and Psychological Measurement

    1 publications · 18 citations

    1

    h-index

  5. The Journal of Experimental Education

    1 publications · 25 citations

    1

    h-index

1–5