Statistical Workflow Automation

Statistical Workflow Automation is a systematic framework in statistical software development that orchestrates and streamlines sequential data analysis tasks—including data preprocessing, model execution, and result documentation—through programmable, reproducible pipelines to minimize manual intervention and enhance computational efficiency, accuracy, and scalability.

10

Publications

412

Citations

33

Authors

22

Institutions

Publications per year

2017–2026

6

Authors

33

  1. CZ
    Chao Zhang

    Emory University, United States

    2 publications · 162 citations

    2

    h-index

  2. DN
    Dana Nickleach

    Emory University, United States

    2 publications · 162 citations

    2

    h-index

  3. YL
    Yuan Liu

    Emory University, United States

    2 publications · 162 citations

    2

    h-index

  4. JK
    Jeanne Kowalski

    Johns Hopkins University, United States

    2 publications · 162 citations

    2

    h-index

  5. JM
    Jeffrey M. Switchenko

    Emory University, United States

    2 publications · 162 citations

    2

    h-index

1–5 of 33

Venues

  1. F1000Research

    2 publications · 162 citations

    2

    h-index

  2. Computers & Geosciences

    CAGEO · 1 publications · 21 citations

    1

    h-index

  3. SMU Scholar (Southern Methodist University)

    Repository · 1 publications · 13 citations

    1

    h-index

  4. Journal of Informetrics

    1 publications · 45 citations

    1

    h-index

  5. Journal of Economic Surveys

    1 publications · 12 citations

    1

    h-index

1–5