Latent Variable Causal Models

Latent Variable Causal Models is a causal modeling framework that integrates unobserved (latent) variables into structural causal models to account for hidden confounding factors while enabling identification and estimation of causal relationships from multi-omics data.

280

Publications

54.1K

Citations

660

Authors

349

Institutions

Publications per year

2017–2026

87

Variants

Latent Variable Causal Modeling

Authors

660

  1. PM
    Peter M. Bentler

    University of California, Los Angeles, United States

    7 publications · 2.2K citations

    7

    h-index

  2. PS
    Peter Spirtes

    Carnegie Mellon University, United States

    6 publications · 372 citations

    6

    h-index

  3. RV
    Riet van Bork

    University of Amsterdam, Netherlands

    6 publications · 574 citations

    6

    h-index

  4. CG
    Clark Glymour

    Carnegie Mellon University, United States

    6 publications · 349 citations

    6

    h-index

  5. GJ
    G. J. Huba

    University of California, Los Angeles, United States

    5 publications · 675 citations

    5

    h-index

1–5 of 660

Venues

  1. Journal of Personality and Social Psychology

    9 publications · 1.7K citations

    9

    h-index

  2. arXiv (Cornell University)

    Repository · 8 publications · 578 citations

    8

    h-index

  3. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 7 publications · 588 citations

    7

    h-index

  4. Journal of the American Statistical Association

    6 publications · 3.4K citations

    6

    h-index

  5. SSRN Electronic Journal

    Repository · 5 publications · 105 citations

    5

    h-index

1–5