First-order Conditional Estimation

First-Order Conditional Estimation is a parameter estimation method in population pharmacokinetic modeling that belongs to the class of nonlinear mixed-effects modeling techniques, distinguished by its use of a first-order approximation to the conditional likelihood of individual parameters given the observed data and population estimates.

34

Publications

1.3K

Citations

142

Authors

77

Institutions

Publications per year

2017–2026

9

Authors

142

  1. FM
    France Mentré

    Inserm, France

    3 publications · 128 citations

    3

    h-index

  2. CM
    Chee M. Ng

    Children's Hospital of Philadelphia, United States

    3 publications · 67 citations

    3

    h-index

  3. YY
    Yoshitaka Yano

    Kyoto Pharmaceutical University, Japan

    2 publications · 300 citations

    2

    h-index

  4. KO
    Katsuhiko Okumura

    Kobe University Hospital, Japan

    2 publications · 300 citations

    2

    h-index

  5. HZ
    HIROSHI ZENDA

    University of Shizuoka, Japan

    2 publications · 300 citations

    2

    h-index

1–5 of 142

Venues

  1. Therapeutic Drug Monitoring

    4 publications · 374 citations

    4

    h-index

  2. Biopharmaceutics & Drug Disposition

    2 publications · 33 citations

    2

    h-index

  3. 2

    h-index

  4. British Journal of Clinical Pharmacology

    BJCP · 2 publications · 36 citations

    2

    h-index

  5. Journal of Multivariate Analysis

    1 publications · 18 citations

    1

    h-index

1–5