Bayesian Structural Equation Models

Bayesian Structural Equation Models is a statistical modeling framework within the class of structural equation models that incorporates Bayesian inference to estimate latent variables and their relationships, distinguishing itself by the explicit use of prior distributions and posterior updating for parameter estimation under uncertainty.

304

Publications

19.1K

Citations

819

Authors

465

Institutions

Publications per year

2017–2026

140

Authors

819

  1. SL
    Sik‐Yum Lee

    Chinese University of Hong Kong, Hong Kong SAR China

    24 publications · 1.5K citations

    20

    h-index

  2. XS
    Xinyuan Song

    Chinese University of Hong Kong, Hong Kong SAR China

    11 publications · 356 citations

    11

    h-index

  3. BM
    Bengt Muthén

    University of California, Los Angeles, United States

    9 publications · 3.5K citations

    9

    h-index

  4. TA
    Tihomir Asparouhov

    Muthén & Muthén (United States), United States

    8 publications · 3.3K citations

    8

    h-index

  5. HH
    Herbert Hoijtink

    Utrecht University, Netherlands

    6 publications · 446 citations

    6

    h-index

1–5 of 819

Venues

  1. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 48 publications · 3.1K citations

    26

    h-index

  2. Frontiers in Psychology

    11 publications · 576 citations

    11

    h-index

  3. Multivariate Behavioral Research

    MBR · 11 publications · 932 citations

    11

    h-index

  4. Psychological Methods

    9 publications · 2.1K citations

    9

    h-index

  5. Psychometrika

    8 publications · 616 citations

    8

    h-index

1–5