Sequential Multiple Testing

Sequential Multiple Testing is a statistical inference procedure that extends sequential analysis to the simultaneous testing of multiple hypotheses, enabling data to be evaluated as it accrues while controlling error rates across a family of tests.

170

Publications

32.1K

Citations

316

Authors

197

Institutions

Publications per year

2017–2026

21

Authors

316

  1. JP
    Juliet Popper Shaffer

    University of California, Berkeley, United States

    4 publications · 1K citations

    4

    h-index

  2. DS
    David Siegmund

    Stanford University, United States

    4 publications · 107 citations

    4

    h-index

  3. AD
    Alex Dmitrienko

    Eli Lilly (United States), United States

    4 publications · 224 citations

    4

    h-index

  4. CJ
    Christopher Jennison

    University of Bath, United Kingdom

    4 publications · 230 citations

    4

    h-index

  5. SK
    Shyamal K. De

    The University of Texas at Dallas, United States

    3 publications · 104 citations

    3

    h-index

1–5 of 316

Venues

  1. Journal of the American Statistical Association

    13 publications · 1.4K citations

    12

    h-index

  2. Biometrika

    11 publications · 462 citations

    11

    h-index

  3. Statistics in Medicine

    9 publications · 681 citations

    10

    h-index

  4. Biometrics

    11 publications · 1K citations

    10

    h-index

  5. Biometrical Journal

    7 publications · 188 citations

    7

    h-index

1–5