Nonlinear Mixed-effects Model Diagnostics

Nonlinear Mixed-Effects Model Diagnostics is a methodological framework within statistical model evaluation that enables the assessment of model adequacy and identification of structural or distributional misspecifications in nonlinear mixed-effects models through systematic examination of residuals, parameter estimates, and predictive performance.

11

Publications

1.9K

Citations

42

Authors

22

Institutions

Publications per year

2017–2026

4

Authors

42

  1. GR
    Gijs R. van den Brink

    Amsterdam UMC Location University of Amsterdam, Netherlands

    1 publications · 147 citations

    1

    h-index

  2. DJ
    Daniel J. Bauer

    University of North Carolina at Chapel Hill, United States

    1 publications · 38 citations

    1

    h-index

  3. AC
    Andrew C. Hooker

    Uppsala University, Sweden

    1 publications · 1.4K citations

    1

    h-index

  4. GD
    Geert D’Haens

    Amsterdam UMC Location University of Amsterdam, Netherlands

    1 publications · 147 citations

    1

    h-index

  5. RD
    Reza Drikvandi

    KU Leuven, Belgium

    1 publications · 14 citations

    1

    h-index

1–5 of 42

Venues

  1. Computational Statistics & Data Analysis

    CSDA · 2 publications · 76 citations

    2

    h-index

  2. Emotion

    1 publications · 89 citations

    1

    h-index

  3. Statistics

    1 publications · 21 citations

    1

    h-index

  4. Annals of Behavioral Medicine

    1 publications · 10 citations

    1

    h-index

  5. Canadian Journal of Forest Research

    1 publications · 46 citations

    1

    h-index

1–5