Likelihood Ratio Tests

Likelihood Ratio Tests is a statistical hypothesis testing method that compares the goodness of fit between two nested models by evaluating the ratio of their maximized likelihoods under the null and alternative hypotheses.

2.8K

Publications

283.8K

Citations

7.9K

Authors

2.4K

Institutions

Publications per year

2017–2026

348

Authors

7.9K

  1. DW
    Donald W. K. Andrews

    Yale University, United States

    18 publications · 8.3K citations

    16

    h-index

  2. GM
    Gauss M. Cordeiro

    Universidade Federal de Pernambuco, Brazil

    13 publications · 537 citations

    12

    h-index

  3. TR
    Tim Robertson

    University of Iowa, United States

    12 publications · 590 citations

    12

    h-index

  4. JB
    John Buckleton

    New Zealand Institute for Public Health and Forensic Science, New Zealand

    11 publications · 339 citations

    11

    h-index

  5. GZ
    Grzegorz Zadora

    Centralne Laboratorium Kryminalistyczne Policji, Poland

    13 publications · 462 citations

    11

    h-index

1–5 of 7.9K

Venues

  1. Journal of the American Statistical Association

    138 publications · 13.7K citations

    51

    h-index

  2. Biometrika

    107 publications · 8.7K citations

    44

    h-index

  3. Biometrics

    93 publications · 9.1K citations

    44

    h-index

  4. The Annals of Statistics

    71 publications · 5.1K citations

    36

    h-index

  5. 32

    h-index

1–5