Interaction Selection

Interaction Selection is a variable selection methodology that specifically identifies and incorporates interaction effects between predictors to determine their collective influence on an outcome, distinguishing it from main effects selection by focusing on multiplicative or joint contributions of variables.

28

Publications

6.5K

Citations

77

Authors

37

Institutions

Publications per year

2017–2026

13

Authors

77

  1. YC
    Yifan Chen

    National University of Defense Technology, China

    2 publications · 62 citations

    2

    h-index

  2. HH
    Hao Helen Zhang

    University of Arizona, United States

    2 publications · 173 citations

    2

    h-index

  3. NH
    Ning Hao

    University of Arizona, United States

    2 publications · 173 citations

    2

    h-index

  4. DL
    Daoji Li

    California State University, Fullerton, United States

    2 publications · 80 citations

    2

    h-index

  5. YF
    Yingying Fan

    University of Southern California, United States

    2 publications · 80 citations

    2

    h-index

1–5 of 77

Venues

  1. 2

    h-index

  2. 1

    h-index

  3. Behavior Research Methods

    BRM · 1 publications · 2.4K citations

    1

    h-index

  4. The American Naturalist

    AN · 1 publications · 314 citations

    1

    h-index

  5. ACM Transactions on Computer-Human Interaction

    TOCHI · 1 publications · 101 citations

    1

    h-index

1–5