Conditional Independence Testing

Conditional Independence Testing is a statistical inference procedure that assesses whether two random variables are independent given a set of conditioning variables, thereby distinguishing itself from unconditional independence tests by explicitly accounting for the influence of specified covariates in determining the dependency structure.

397

Publications

28.4K

Citations

760

Authors

389

Institutions

Publications per year

2017–2026

91

Authors

760

  1. SZ
    Shuigeng Zhou

    Fudan University, China

    6 publications · 116 citations

    6

    h-index

  2. JG
    Jihong Guan

    Tongji University, China

    6 publications · 116 citations

    6

    h-index

  3. LS
    Liangjun Su

    Singapore Management University, Singapore

    6 publications · 548 citations

    6

    h-index

  4. LA
    Leo A. Goodman

    University of Chicago, United States

    5 publications · 1.1K citations

    5

    h-index

  5. JP
    Jonas Peters

    ETH Zurich, Switzerland

    5 publications · 643 citations

    5

    h-index

1–5 of 760

Venues

  1. arXiv (Cornell University)

    Repository · 25 publications · 1.1K citations

    17

    h-index

  2. Journal of the American Statistical Association

    22 publications · 1.9K citations

    16

    h-index

  3. Journal of Multivariate Analysis

    19 publications · 500 citations

    13

    h-index

  4. Biometrics

    13 publications · 1.6K citations

    12

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 13 publications · 372 citations

    12

    h-index

1–5