Multilevel Latent Variable Models

Multilevel Latent Variable Models is a statistical modeling framework that extends latent variable models by incorporating hierarchically structured data through multiple levels of random effects, thereby accounting for both unobserved heterogeneity and nested data dependencies within a single integrated model.

505

Publications

55.7K

Citations

1.1K

Authors

523

Institutions

Publications per year

2017–2026

175

Authors

1.1K

  1. BM
    Bengt Muthén

    University of California, Los Angeles, United States

    19 publications · 8.4K citations

    18

    h-index

  2. JK
    Jeroen K. Vermunt

    Tilburg University, Netherlands

    15 publications · 1.2K citations

    13

    h-index

  3. HW
    Herbert W. Marsh

    Western Sydney University, Australia

    11 publications · 3K citations

    11

    h-index

  4. OL
    Oliver Lüdtke

    Leibniz Institute for Science and Mathematics Education, Germany

    9 publications · 2.4K citations

    9

    h-index

  5. TA
    Tihomir Asparouhov

    Muthén & Muthén (United States), United States

    8 publications · 5.2K citations

    8

    h-index

1–5 of 1.1K

Venues

  1. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 35 publications · 6.2K citations

    25

    h-index

  2. Multivariate Behavioral Research

    MBR · 18 publications · 1.6K citations

    15

    h-index

  3. Psychological Methods

    13 publications · 2.8K citations

    13

    h-index

  4. Journal of Educational and Behavioral Statistics

    14 publications · 1.1K citations

    13

    h-index

  5. Psychometrika

    12 publications · 2.4K citations

    12

    h-index

1–5