Multinomial Sample Selection

Multinomial Sample Selection is a sample selection model that extends the standard binary selection framework to accommodate multiple non-ordered outcome categories by modeling the joint distribution of a multinomial selection process and a continuous outcome equation.

56

Publications

2.2K

Citations

132

Authors

99

Institutions

Publications per year

2017–2026

12

Authors

132

  1. KA
    Khursheed Alam

    Aligarh Muslim University, India

    5 publications · 121 citations

    5

    h-index

  2. DG
    David Goldsman

    Georgia Institute of Technology, United States

    3 publications · 78 citations

    3

    h-index

  3. ST
    Steven T. Yen

    University of Tennessee at Knoxville, United States

    2 publications · 34 citations

    2

    h-index

  4. JB
    Judith Bromberg

    University of Michigan, United States

    2 publications · 30 citations

    2

    h-index

  5. RE
    Robert E. Bechhofer

    Cornell University, United States

    2 publications · 65 citations

    2

    h-index

1–5 of 132

Venues

  1. The American Statistician

    4 publications · 300 citations

    4

    h-index

  2. 2

    h-index

  3. Biometrics

    2 publications · 31 citations

    2

    h-index

  4. Technometrics

    2 publications · 43 citations

    2

    h-index

  5. 2

    h-index

1–5