Binary Outcome Sample Size

Binary Outcome Sample Size is a statistical determination method that specifies the minimum number of observations required to achieve predefined levels of power and significance when the outcome variable of interest is dichotomous in nature.

56

Publications

3.7K

Citations

162

Authors

128

Institutions

Publications per year

2017–2026

12

Authors

162

  1. RD
    Richard D Riley

    Keele University, United Kingdom

    3 publications · 430 citations

    3

    h-index

  2. PR
    Patrick Royston

    MRC Clinical Trials Unit at UCL, United Kingdom

    3 publications · 92 citations

    3

    h-index

  3. NT
    Niansheng Tang

    Yunnan University, China

    3 publications · 40 citations

    3

    h-index

  4. MT
    Man‐Lai Tang

    Hong Kong Baptist University, Hong Kong SAR China

    3 publications · 40 citations

    3

    h-index

  5. SB
    Stephen Burgess

    University of Cambridge, United Kingdom

    2 publications · 693 citations

    2

    h-index

1–5 of 162

Venues

  1. Statistics in Medicine

    16 publications · 942 citations

    15

    h-index

  2. Biometrics

    3 publications · 46 citations

    3

    h-index

  3. 3

    h-index

  4. Journal of Biopharmaceutical Statistics

    JBS · 3 publications · 87 citations

    3

    h-index

  5. Controlled Clinical Trials

    2 publications · 103 citations

    2

    h-index

1–5