Multidimensional Model Fit

Multidimensional Model Fit is a formal assessment framework that evaluates the degree to which a statistical model simultaneously captures multiple latent dimensions or constructs in relation to observed data, distinguishing itself from unidimensional fit approaches by accounting for interdependent, non-redundant sources of model variation.

458

Publications

30.8K

Citations

4.4K

Authors

908

Institutions

Publications per year

2017–2026

135

Authors

4.4K

  1. CS
    Craig S. Neumann

    University of North Texas, United States

    6 publications · 1K citations

    6

    h-index

  2. DH
    David H. Gleaves

    Texas A&M University, United States

    5 publications · 365 citations

    5

    h-index

  3. LE
    Luís Eduardo Garrido

    Pontificia Universidad Católica Madre y Maestra, Dominican Republic

    4 publications · 304 citations

    4

    h-index

  4. AJ
    Andrew J. Martin

    UNSW Sydney, Australia

    4 publications · 1K citations

    4

    h-index

  5. RD
    Robert D. Hare

    University of British Columbia, Canada

    4 publications · 495 citations

    4

    h-index

1–5 of 4.4K

Venues

  1. Psychological Assessment

    17 publications · 1.6K citations

    16

    h-index

  2. Journal of Personality Assessment

    9 publications · 545 citations

    9

    h-index

  3. Assessment

    ASM · 9 publications · 1.6K citations

    9

    h-index

  4. PLoS ONE

    7 publications · 226 citations

    7

    h-index

  5. Educational and Psychological Measurement

    6 publications · 409 citations

    6

    h-index

1–5