Test Statistics

Test Statistics is a formal metric within Bayesian model checking that quantifies the discrepancy between observed data and the predictions of a posited model, distinguishing itself by its reliance on posterior predictive distributions to assess model adequacy.

2.8K

Publications

469.8K

Citations

4.8K

Authors

1.7K

Institutions

Publications per year

2017–2026

430

Authors

4.8K

  1. PM
    Peter M. Bentler

    University of California, Los Angeles, United States

    19 publications · 9.3K citations

    16

    h-index

  2. EW
    Eric‐Jan Wagenmakers

    University of Amsterdam, Netherlands

    17 publications · 5.9K citations

    15

    h-index

  3. KY
    Ke‐Hai Yuan

    University of Notre Dame, United States

    14 publications · 2.2K citations

    14

    h-index

  4. PP
    Pierre Perrón

    Boston University, United States

    13 publications · 11.1K citations

    13

    h-index

  5. DW
    Donald W. K. Andrews

    Yale University, United States

    13 publications · 1.3K citations

    13

    h-index

1–5 of 4.8K

Venues

  1. Journal of the American Statistical Association

    207 publications · 20.1K citations

    69

    h-index

  2. The Annals of Statistics

    96 publications · 21.7K citations

    46

    h-index

  3. Biometrics

    99 publications · 86.1K citations

    42

    h-index

  4. Biometrika

    82 publications · 6.9K citations

    37

    h-index

  5. Statistics in Medicine

    73 publications · 8.2K citations

    34

    h-index

1–5