Probabilistic Sensitivity Analysis

Probabilistic Sensitivity Analysis is a statistical methodology within sensitivity analysis that quantifies the effect of uncertainty in model inputs, characterized by probability distributions, on the variability of model outputs, thereby distinguishing itself from deterministic approaches by incorporating probabilistic representations of input parameter uncertainty.

771

Publications

37.4K

Citations

3.2K

Authors

1.3K

Institutions

Publications per year

2017–2026

314

Authors

3.2K

  1. MG
    M. G. Myriam Hunink

    Erasmus MC, Netherlands

    9 publications · 453 citations

    9

    h-index

  2. EB
    Emanuele Borgonovo

    Bocconi University, Italy

    8 publications · 504 citations

    8

    h-index

  3. JE
    Jeremy E. Oakley

    University of Sheffield, United Kingdom

    7 publications · 1.7K citations

    7

    h-index

  4. BW
    Bin Wu

    Renji Hospital, China

    6 publications · 180 citations

    6

    h-index

  5. MF
    Matthias F. Froelich

    University Medical Centre Mannheim, Germany

    6 publications · 146 citations

    6

    h-index

1–5 of 3.2K

Venues

  1. Medical Decision Making

    MDM · 31 publications · 3.1K citations

    23

    h-index

  2. Reliability Engineering & System Safety

    24 publications · 1.5K citations

    20

    h-index

  3. PLoS ONE

    30 publications · 830 citations

    19

    h-index

  4. Journal of Medical Economics

    JME · 14 publications · 407 citations

    13

    h-index

  5. 12

    h-index

1–5