Propensity Score Machine Learning

Propensity Score Machine Learning is a machine learning framework that estimates the conditional probability of treatment assignment given observed covariates to enable causal inference by balancing confounding variables in observational studies.

45

Publications

3.7K

Citations

202

Authors

115

Institutions

Publications per year

2017–2026

33

Authors

202

  1. DM
    Dominique Monlezun

    Tulane University, United States

    4 publications · 133 citations

    4

    h-index

  2. PR
    Paul R. Yarnold

    Northwestern University, United States

    4 publications · 97 citations

    4

    h-index

  3. AL
    Ariel Linden

    Linden Photonics (United States), United States

    4 publications · 97 citations

    4

    h-index

  4. CI
    Cezar Iliescu

    The University of Texas MD Anderson Cancer Center, United States

    3 publications · 64 citations

    3

    h-index

  5. JL
    Justin Lessler

    Johns Hopkins University, United States

    2 publications · 1.4K citations

    2

    h-index

1–5 of 202

Venues

  1. Journal of Evaluation in Clinical Practice

    4 publications · 97 citations

    4

    h-index

  2. Statistics in Medicine

    3 publications · 1K citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 132 citations

    3

    h-index

  4. BMC Medical Research Methodology

    2 publications · 36 citations

    2

    h-index

  5. Statistical Methods in Medical Research

    2 publications · 81 citations

    2

    h-index

1–5