Bayesian Partial Credit Model

The Bayesian Partial Credit Model is a latent trait model within item response theory that extends the partial credit model by incorporating Bayesian inference methods to estimate parameters through the specification of prior distributions, thereby distinguishing itself from classical frequentist approaches in the handling of parameter uncertainty and model estimation.

15

Publications

1.2K

Citations

51

Authors

38

Institutions

Publications per year

2017–2026

4

Authors

51

  1. YD
    Yannis Dionyssiotis

    National and Kapodistrian University of Athens, Greece

    1 publications · 24 citations

    1

    h-index

  2. ML
    M. Le Fort

    Centre Hospitalier Universitaire de Nantes, France

    1 publications · 24 citations

    1

    h-index

  3. HS
    Hyun-Jung Sung

    Pearson (United States), United States

    1 publications · 76 citations

    1

    h-index

  4. MA
    Marcelo A. da Silva

    Universidade de São Paulo, Brazil

    1 publications · 16 citations

    1

    h-index

  5. NS
    Ningzhong Shi

    Northeast Normal University, China

    1 publications · 22 citations

    1

    h-index

1–5 of 51

Venues

  1. Applied Measurement in Education

    2 publications · 38 citations

    2

    h-index

  2. Psychometrika

    2 publications · 118 citations

    2

    h-index

  3. Applied Psychological Measurement

    2 publications · 92 citations

    2

    h-index

  4. Journal of Statistical Software

    JSS · 1 publications · 740 citations

    1

    h-index

  5. Statistics in Medicine

    1 publications · 24 citations

    1

    h-index

1–5