Bayesian Causality Assessment

Bayesian Causality Assessment is a formal probabilistic framework for evaluating causal relationships among variables by updating prior beliefs with observed evidence according to Bayes' theorem, distinguished from other causal assessment methods by its explicit incorporation of uncertainty and subjective priors in the inference process.

12

Publications

392

Citations

45

Authors

24

Institutions

Publications per year

2017–2026

2

Authors

45

  1. KL
    Krista L. Lanctôt

    Sunnybrook Health Science Centre, Canada

    2 publications · 69 citations

    2

    h-index

  2. DA
    David A. Lane

    Charing Cross Hospital, United Kingdom

    2 publications · 51 citations

    2

    h-index

  3. CA
    Claudio A. Naranjo

    University of Toronto, Canada

    2 publications · 69 citations

    2

    h-index

  4. PP
    Pedro Pereira Rodrigues

    Universidade do Porto, Portugal

    1 publications · 26 citations

    1

    h-index

  5. FX
    Fuzhong Xue

    Shandong University, China

    1 publications · 76 citations

    1

    h-index

1–5 of 45

Venues

  1. Pharmacoepidemiology and Drug Safety

    2 publications · 29 citations

    2

    h-index

  2. The Journal of Clinical Pharmacology

    2 publications · 69 citations

    2

    h-index

  3. Frontiers in Pharmacology

    1 publications · 20 citations

    1

    h-index

  4. PubMed

    Repository · 1 publications · 10 citations

    1

    h-index

  5. BMJ Open

    1 publications · 76 citations

    1

    h-index

1–5