Longitudinal Data Analysis

Longitudinal Data Analysis is a branch of statistical methodology that focuses on modeling and inference for data consisting of repeated measurements on the same observational units over time, distinguishing itself by explicitly accounting for within-unit correlation, time-varying covariates, and temporal dependence in order to characterize change and assess associations between risk factors and outcomes.

4.3K

Publications

421.2K

Citations

9.5K

Authors

2.5K

Institutions

Publications per year

2017–2026

1K

Authors

9.5K

  1. GM
    Geert Molenberghs

    Hasselt University, Belgium

    68 publications · 4.7K citations

    32

    h-index

  2. DH
    Donald Hedeker

    University of Illinois Chicago, United States

    26 publications · 4.7K citations

    25

    h-index

  3. GV
    Geert Verbeke

    KU Leuven, Belgium

    35 publications · 2.4K citations

    24

    h-index

  4. DR
    Dimitris Rizopoulos

    Erasmus MC, Netherlands

    30 publications · 2.9K citations

    23

    h-index

  5. EL
    Emmanuel Lesaffre

    KU Leuven, Belgium

    29 publications · 2.3K citations

    22

    h-index

1–5 of 9.5K

Venues

  1. Journal of the American Statistical Association

    183 publications · 25.8K citations

    79

    h-index

  2. Statistics in Medicine

    392 publications · 23.9K citations

    72

    h-index

  3. Biometrics

    227 publications · 37.9K citations

    71

    h-index

  4. Psychological Methods

    76 publications · 12.5K citations

    48

    h-index

  5. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 93 publications · 8K citations

    41

    h-index

1–5