Conditional Dependence Estimation

Conditional Dependence Estimation is a statistical inference method that identifies and quantifies the dependence between random variables given the values of other variables in a network structure, distinguishing it from marginal or pairwise dependence estimation by explicitly conditioning on confounding or mediating factors.

249

Publications

20.6K

Citations

658

Authors

401

Institutions

Publications per year

2017–2026

85

Authors

658

  1. DR
    Donald R. Williams

    University of California, Davis, United States

    4 publications · 176 citations

    4

    h-index

  2. HX
    Huiping Xu

    Indiana University – Purdue University Indianapolis, United States

    4 publications · 63 citations

    4

    h-index

  3. DW
    Daniela Witten

    University of Washington, United States

    4 publications · 295 citations

    4

    h-index

  4. SL
    Su‐In Lee

    University of Washington, United States

    4 publications · 344 citations

    4

    h-index

  5. ND
    Nandini Dendukuri

    McGill University, Canada

    4 publications · 688 citations

    4

    h-index

1–5 of 658

Venues

  1. Journal of the American Statistical Association

    10 publications · 1.6K citations

    10

    h-index

  2. Statistics in Medicine

    8 publications · 372 citations

    8

    h-index

  3. Biometrics

    8 publications · 2.5K citations

    8

    h-index

  4. arXiv (Cornell University)

    Repository · 8 publications · 231 citations

    8

    h-index

  5. Biometrika

    7 publications · 263 citations

    7

    h-index

1–5