Random-effects Network Meta-analysis

Random-Effects Network Meta-Analysis is a statistical method within the class of network meta-analytic models that incorporates both within-study and between-study variability by assuming that treatment effects vary across studies according to a specified distribution, thereby allowing generalization beyond the included studies.

55

Publications

4.1K

Citations

344

Authors

189

Institutions

Publications per year

2017–2026

42

Variants

Random-effects Nma

Authors

344

  1. AC
    Andrea Cipriani

    University of Oxford, United Kingdom

    3 publications · 922 citations

    3

    h-index

  2. HN
    Hisashi Noma

    The Institute of Statistical Mathematics, Japan

    3 publications · 905 citations

    3

    h-index

  3. JB
    Jean Bourhis

    Institut Gustave Roussy, France

    2 publications · 388 citations

    2

    h-index

  4. IR
    Ian R. White

    MRC Biostatistics Unit, United Kingdom

    2 publications · 346 citations

    2

    h-index

  5. GS
    Georgia Salanti

    University of Bern, Switzerland

    2 publications · 91 citations

    2

    h-index

1–5 of 344

Venues

  1. Statistics in Medicine

    4 publications · 366 citations

    4

    h-index

  2. PLoS ONE

    3 publications · 235 citations

    3

    h-index

  3. Biometrical Journal

    2 publications · 61 citations

    2

    h-index

  4. EClinicalMedicine

    2 publications · 35 citations

    2

    h-index

  5. Journal of Clinical Oncology

    2 publications · 388 citations

    2

    h-index

1–5