Adaptive Hypothesis Testing

Adaptive Hypothesis Testing is a statistical inference framework within adaptive experimental designs that dynamically modifies hypotheses or testing procedures based on accumulating data while preserving Type I error control.

252

Publications

13.9K

Citations

445

Authors

287

Institutions

Publications per year

2017–2026

61

Authors

445

  1. WJ
    Wim J. van der Linden

    University of Twente, Netherlands

    8 publications · 724 citations

    8

    h-index

  2. MP
    Martin Posch

    Medical University of Vienna, Austria

    8 publications · 341 citations

    8

    h-index

  3. RV
    Robert V. Hogg

    University of Iowa, United States

    5 publications · 376 citations

    5

    h-index

  4. DJ
    David J. Weiss

    University of Minnesota, United States

    5 publications · 385 citations

    5

    h-index

  5. HB
    Herbert Büning

    Freie Universität Berlin, Germany

    5 publications · 95 citations

    5

    h-index

1–5 of 445

Venues

  1. Biometrical Journal

    16 publications · 627 citations

    14

    h-index

  2. Psychometrika

    12 publications · 878 citations

    12

    h-index

  3. Statistics in Medicine

    12 publications · 525 citations

    11

    h-index

  4. arXiv (Cornell University)

    Repository · 8 publications · 434 citations

    8

    h-index

  5. 6

    h-index

1–5