Posterior Predictive Checking

Posterior Predictive Checking is a Bayesian model validation technique that assesses the adequacy of a fitted model by comparing observed data to the distribution of replicated data generated from the posterior predictive distribution.

78

Publications

7.2K

Citations

154

Authors

114

Institutions

Publications per year

2017–2026

14

Authors

154

  1. SS
    Sandip Sinharay

    Educational Testing Service, United States

    9 publications · 731 citations

    9

    h-index

  2. AG
    Andrew Gelman

    Columbia University, United States

    4 publications · 592 citations

    4

    h-index

  3. IV
    Iven Van Mechelen

    KU Leuven, Belgium

    3 publications · 312 citations

    3

    h-index

  4. RL
    Roy Levy

    Arizona State University, United States

    3 publications · 140 citations

    3

    h-index

  5. JB
    John B. Carlin

    The University of Melbourne, Australia

    3 publications · 349 citations

    3

    h-index

1–5 of 154

Venues

  1. Applied Psychological Measurement

    7 publications · 472 citations

    7

    h-index

  2. Biometrics

    4 publications · 205 citations

    4

    h-index

  3. ETS Research Report Series

    3 publications · 76 citations

    3

    h-index

  4. Statistics in Medicine

    3 publications · 215 citations

    3

    h-index

  5. 3

    h-index

1–5