Generalizability Theory

Generalizability theory is a statistical framework for assessing measurement dependability that simultaneously estimates multiple sources of variance to determine the generalizability of behavioral observations across varying measurement conditions.

1.5K

Publications

199.5K

Citations

2.7K

Authors

998

Institutions

Publications per year

2017–2026

213

Authors

2.7K

  1. RL
    Robert L. Brennan

    University of Iowa, United States

    22 publications · 1.7K citations

    20

    h-index

  2. WP
    Walter P. Vispoel

    University of Iowa, United States

    14 publications · 356 citations

    14

    h-index

  3. GA
    George A. Marcoulides

    California State University, Fullerton, United States

    14 publications · 387 citations

    12

    h-index

  4. ON
    Oleg N. Medvedev

    Auckland University of Technology, New Zealand

    11 publications · 323 citations

    11

    h-index

  5. FL
    Frank L. Schmidt

    University of Iowa, United States

    9 publications · 1.8K citations

    9

    h-index

1–5 of 2.7K

Venues

  1. The Annals of Statistics

    45 publications · 16.8K citations

    28

    h-index

  2. Journal of the American Statistical Association

    34 publications · 2.9K citations

    26

    h-index

  3. The Annals of Mathematical Statistics

    35 publications · 3.3K citations

    23

    h-index

  4. Educational and Psychological Measurement

    41 publications · 3.6K citations

    21

    h-index

  5. Psychological Methods

    24 publications · 3.6K citations

    20

    h-index

1–5

See also

Generalizability Theory

Core Methods

Variance Facets

Dependability Coefficients

Study Designs

Applications