Longitudinal Missing Data

Longitudinal Missing Data is a type of missing data pattern that occurs in longitudinal studies where repeated measurements over time are partially unobserved, distinguished by its temporal structure and potential dependence of missingness on past or future observed and unobserved variables.

614

Publications

38.2K

Citations

1.5K

Authors

733

Institutions

Publications per year

2017–2026

125

Authors

1.5K

  1. GM
    Geert Molenberghs

    Hasselt University, Belgium

    37 publications · 2.9K citations

    24

    h-index

  2. MG
    Michael G. Kenward

    London School of Hygiene & Tropical Medicine, United Kingdom

    13 publications · 1.2K citations

    13

    h-index

  3. GV
    Geert Verbeke

    KU Leuven, Belgium

    14 publications · 521 citations

    13

    h-index

  4. GM
    Garrett M. Fitzmaurice

    Harvard University, United States

    12 publications · 637 citations

    12

    h-index

  5. CM
    Craig Mallinckrodt

    Eli Lilly (United States), United States

    10 publications · 869 citations

    10

    h-index

1–5 of 1.5K

Venues

  1. Statistics in Medicine

    82 publications · 4.7K citations

    36

    h-index

  2. Biometrics

    45 publications · 2.9K citations

    30

    h-index

  3. Journal of the American Statistical Association

    19 publications · 1.2K citations

    17

    h-index

  4. Biostatistics

    16 publications · 1.4K citations

    15

    h-index

  5. BMC Medical Research Methodology

    14 publications · 808 citations

    13

    h-index

1–5