Missing Covariate Data

Missing Covariate Data is a type of data incompleteness in which covariate values are absent for certain observations in a statistical or mathematical model, thereby compromising the complete representation of the relationship between predictors and outcomes.

326

Publications

32.5K

Citations

722

Authors

362

Institutions

Publications per year

2017–2026

56

Authors

722

  1. JG
    Joseph G. Ibrahim

    University of North Carolina at Chapel Hill, United States

    25 publications · 2.3K citations

    21

    h-index

  2. SR
    Stuart R. Lipsitz

    Brigham and Women's Hospital, United States

    18 publications · 1.7K citations

    17

    h-index

  3. IR
    Ian R. White

    MRC Biostatistics Unit, United Kingdom

    8 publications · 4.3K citations

    8

    h-index

  4. RJ
    Roderick J. A. Little

    University of Michigan, United States

    8 publications · 1.6K citations

    8

    h-index

  5. MS
    Margaret S. Pepe

    Fred Hutch Cancer Center, United States

    7 publications · 550 citations

    7

    h-index

1–5 of 722

Venues

  1. Journal of the American Statistical Association

    31 publications · 5.8K citations

    27

    h-index

  2. Statistics in Medicine

    37 publications · 5.7K citations

    25

    h-index

  3. Biometrics

    25 publications · 1.2K citations

    22

    h-index

  4. Biometrika

    23 publications · 2.8K citations

    16

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 8 publications · 179 citations

    8

    h-index

1–5