Dynamic Multilevel Models

Dynamic Multilevel Models is a Bayesian multilevel modeling framework that extends static hierarchical structures by incorporating time-varying parameters and latent processes to capture temporal dynamics within and across levels of nested data.

72

Publications

5.3K

Citations

199

Authors

124

Institutions

Publications per year

2017–2026

29

Variants

Dynamic Multilevel Modeling

Authors

199

  1. HH
    Hadi Hajibeygi

    Delft University of Technology, Netherlands

    4 publications · 162 citations

    4

    h-index

  2. AH
    Arnd Huchzermeier

    WHU – Otto Beisheim School of Management, Germany

    3 publications · 171 citations

    3

    h-index

  3. SN
    Serena Ng

    Columbia University, United States

    3 publications · 182 citations

    3

    h-index

  4. MK
    Manfred Krafft

    University of Münster, Germany

    3 publications · 171 citations

    3

    h-index

  5. RE
    Ralf Elsner

    University of Münster, Germany

    3 publications · 171 citations

    3

    h-index

1–5 of 199

Venues

  1. Psychological Methods

    3 publications · 101 citations

    3

    h-index

  2. Journal of Computational Physics

    3 publications · 142 citations

    3

    h-index

  3. Organizational Psychology Review

    2 publications · 85 citations

    2

    h-index

  4. Organizational Research Methods

    ORM · 2 publications · 60 citations

    2

    h-index

  5. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 2 publications · 315 citations

    2

    h-index

1–5