Exact Inference Under Sparse Data

Exact Inference Under Sparse Data is a statistical methodology for performing rigorous hypothesis testing and confidence interval estimation in categorical data analysis when sample sizes are too small or the data exhibit excessive zeros, such that asymptotic assumptions fail and exact computation of permutation or conditional distributions becomes necessary.

48

Publications

3.8K

Citations

132

Authors

71

Institutions

Publications per year

2017–2026

11

Authors

132

  1. CR
    Cyrus R. Mehta

    Cytel (United States), United States

    5 publications · 315 citations

    5

    h-index

  2. KF
    Karim F. Hirji

    University of California, Los Angeles, United States

    3 publications · 205 citations

    3

    h-index

  3. MV
    Mark van der Wilk

    University of Cambridge, United Kingdom

    2 publications · 36 citations

    2

    h-index

  4. CE
    Carl Edward Rasmussen

    University of Cambridge, United Kingdom

    2 publications · 36 citations

    2

    h-index

  5. AA
    Anastasios A. Tsiatis

    North Carolina State University, United States

    2 publications · 134 citations

    2

    h-index

1–5 of 132

Venues

  1. arXiv (Cornell University)

    Repository · 7 publications · 894 citations

    7

    h-index

  2. Biometrics

    3 publications · 122 citations

    3

    h-index

  3. The American Statistician

    2 publications · 134 citations

    2

    h-index

  4. Journal of Econometrics

    1 publications · 71 citations

    1

    h-index

  5. Computational Statistics & Data Analysis

    CSDA · 1 publications · 20 citations

    1

    h-index

1–5