Time-varying Random Effects

Time-Varying Random Effects is a statistical modeling construct in random effects analysis that allows individual-specific deviations from the population average to change over time, thereby capturing within-subject variability that evolves dynamically across measurement occasions.

47

Publications

2.6K

Citations

114

Authors

94

Institutions

Publications per year

2017–2026

6

Authors

114

  1. PS
    Peter Schmidt

    Michigan State University, United States

    2 publications · 311 citations

    2

    h-index

  2. PA
    P. A. V. B. Swamy

    Federal Reserve, United States

    2 publications · 71 citations

    2

    h-index

  3. SC
    Seung C. Ahn

    Arizona State University, United States

    2 publications · 311 citations

    2

    h-index

  4. YH
    Young Hoon Lee

    Sogang University, South Korea

    2 publications · 311 citations

    2

    h-index

  5. DH
    Donald Hedeker

    University of Illinois Chicago, United States

    1 publications · 58 citations

    1

    h-index

1–5 of 114

Venues

  1. Psychological Methods

    3 publications · 321 citations

    3

    h-index

  2. Scandinavian Journal of Statistics

    3 publications · 102 citations

    3

    h-index

  3. Technometrics

    3 publications · 99 citations

    3

    h-index

  4. SSRN Electronic Journal

    Repository · 2 publications · 44 citations

    2

    h-index

  5. Statistics in Medicine

    2 publications · 146 citations

    2

    h-index

1–5