Variable Selection For Heterogeneity

Variable Selection for Heterogeneity is a methodological framework within causal inference that identifies covariates which systematically modify treatment effects in order to distinguish heterogeneous from homogeneous response patterns across subpopulations.

23

Publications

1.1K

Citations

62

Authors

54

Institutions

Publications per year

2017–2026

5

Authors

62

  1. HL
    Heng Lian

    Nanyang Technological University, Singapore

    4 publications · 126 citations

    4

    h-index

  2. JL
    Jin Liu

    Duke-NUS Medical School, Singapore

    2 publications · 24 citations

    2

    h-index

  3. GL
    Gaorong Li

    Beijing University of Technology, China

    2 publications · 74 citations

    2

    h-index

  4. SZ
    Sanguo Zhang

    University of Chinese Academy of Sciences, China

    2 publications · 24 citations

    2

    h-index

  5. SM
    Shuangge Ma

    Yale University, United States

    2 publications · 24 citations

    2

    h-index

1–5 of 62

Venues

  1. Journal of Econometrics

    2 publications · 51 citations

    2

    h-index

  2. Statistica Sinica

    1 publications · 14 citations

    1

    h-index

  3. Metrika

    1 publications · 11 citations

    1

    h-index

  4. Statistical Methods in Medical Research

    1 publications · 179 citations

    1

    h-index

  5. Scandinavian Journal of Statistics

    1 publications · 22 citations

    1

    h-index

1–5