Nested Data Structures

Nested Data Structures is a data organization paradigm in which observational units are hierarchically grouped into clusters such that lower-level units are wholly contained within higher-level units, thereby inducing dependency structures that violate the assumption of independence in conventional statistical analyses.

133

Publications

9.3K

Citations

358

Authors

179

Institutions

Publications per year

2017–2026

40

Variants

Hierarchical DataMultilevel Data

Authors

358

  1. GE
    Guy E. Blelloch

    Carnegie Mellon University, United States

    4 publications · 459 citations

    4

    h-index

  2. JC
    Jonathan C. Hardwick

    Carnegie Mellon University, United States

    4 publications · 356 citations

    4

    h-index

  3. TP
    Tony Plate

    University of Toronto, Canada

    3 publications · 202 citations

    3

    h-index

  4. SC
    Siddhartha Chatterjee

    Carnegie Mellon University, United States

    3 publications · 345 citations

    3

    h-index

  5. MZ
    Marco Zagha

    Carnegie Mellon University, United States

    3 publications · 345 citations

    3

    h-index

1–5 of 358

Venues

  1. Educational and Psychological Measurement

    4 publications · 152 citations

    4

    h-index

  2. Multivariate Behavioral Research

    MBR · 4 publications · 674 citations

    3

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 3 publications · 202 citations

    3

    h-index

  4. Journal of Computer and System Sciences

    3 publications · 106 citations

    3

    h-index

  5. Bioinformatics

    2 publications · 182 citations

    2

    h-index

1–5