Multivariate Generalizability Analysis

Multivariate Generalizability Analysis is a statistical methodology within generalizability theory that extends univariate approaches by simultaneously assessing the reliability and sources of measurement error across multiple dependent variables or facets in a single study design.

47

Publications

2.3K

Citations

110

Authors

68

Institutions

Publications per year

2017–2026

7

Authors

110

  1. BE
    Brian E. Clauser

    National Board of Medical Examiners, United States

    5 publications · 149 citations

    5

    h-index

  2. PH
    Polina Harik

    National Board of Medical Examiners, United States

    4 publications · 135 citations

    4

    h-index

  3. NM
    Noreen M. Webb

    University of California, Los Angeles, United States

    3 publications · 234 citations

    3

    h-index

  4. BL
    Brian Lakey

    Wayne State University, United States

    3 publications · 466 citations

    3

    h-index

  5. AF
    Adam Finn

    University of Bristol, United Kingdom

    3 publications · 70 citations

    3

    h-index

1–5 of 110

Venues

  1. Educational and Psychological Measurement

    5 publications · 123 citations

    5

    h-index

  2. Journal of Educational Measurement

    4 publications · 132 citations

    4

    h-index

  3. Psychological Methods

    3 publications · 349 citations

    3

    h-index

  4. Teaching and Learning in Medicine

    2 publications · 33 citations

    2

    h-index

  5. Language Testing

    2 publications · 143 citations

    2

    h-index

1–5