Hierarchical Data Modeling

Hierarchical Data Modeling is a data modeling approach that organizes data elements into a tree-like structure where each data entity, except the root, has exactly one parent entity and may have multiple child entities, thereby representing one-to-many relationships in a multilevel containment hierarchy.

234

Publications

16.2K

Citations

656

Authors

310

Institutions

Publications per year

2017–2026

45

Authors

656

  1. HG
    Harvey Goldstein

    University of Bristol, United Kingdom

    6 publications · 786 citations

    6

    h-index

  2. GM
    Geert Molenberghs

    Hasselt University, Belgium

    5 publications · 99 citations

    5

    h-index

  3. BP
    Bradley P. Carlin

    University of Minnesota, United States

    4 publications · 198 citations

    4

    h-index

  4. BS
    Ben Shneiderman

    University of Maryland, College Park, United States

    3 publications · 179 citations

    3

    h-index

  5. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    3 publications · 243 citations

    3

    h-index

1–5 of 656

Venues

  1. 5

    h-index

  2. Statistics in Medicine

    4 publications · 89 citations

    4

    h-index

  3. 4

    h-index

  4. Biometrics

    4 publications · 134 citations

    4

    h-index

  5. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 4 publications · 632 citations

    4

    h-index

1–5