Power Under Missing Data

Power Under Missing Data is a statistical metric that quantifies the probability of correctly rejecting a false null hypothesis in the presence of incomplete data, thereby reflecting the efficacy of a hypothesis test when observations are partially observed due to missingness mechanisms.

40

Publications

2.1K

Citations

114

Authors

70

Institutions

Publications per year

2017–2026

8

Authors

114

  1. DS
    Dinesh S. Bhoj

    Rutgers, The State University of New Jersey, United States

    2 publications · 29 citations

    2

    h-index

  2. SC
    Sung C. Choi

    Virginia Commonwealth University Medical Center, United States

    2 publications · 62 citations

    2

    h-index

  3. ML
    Melanie L. Bell

    University of Arizona, United States

    2 publications · 92 citations

    2

    h-index

  4. TD
    Todd D. Little

    University of Kansas, United States

    2 publications · 320 citations

    2

    h-index

  5. JH
    Jean-Benoît Hardouin

    Nantes Université, France

    1 publications · 19 citations

    1

    h-index

1–5 of 114

Venues

  1. Statistics in Medicine

    6 publications · 251 citations

    6

    h-index

  2. Biometrical Journal

    3 publications · 54 citations

    3

    h-index

  3. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 3 publications · 198 citations

    3

    h-index

  4. 2

    h-index

  5. Biometrika

    2 publications · 29 citations

    2

    h-index

1–5