Bayesian Three-parameter Logistic Model

The Bayesian Three-Parameter Logistic Model is a Bayesian extension of the three-parameter logistic item response theory model that incorporates prior distributions on item parameters—discrimination, difficulty, and pseudo-guessing—to estimate latent trait levels while formally quantifying uncertainty through posterior inference.

24

Publications

924

Citations

62

Authors

41

Institutions

Publications per year

2017–2026

8

Authors

62

  1. JL
    Jane Law

    University of Waterloo, Canada

    2 publications · 108 citations

    2

    h-index

  2. RH
    Robert Haining

    University of Sheffield, United Kingdom

    2 publications · 108 citations

    2

    h-index

  3. ET
    Eric T. Bradlow

    University of Pennsylvania, United States

    1 publications · 12 citations

    1

    h-index

  4. YF
    Yutaka Fujiwara

    Tokyo National Hospital, Japan

    1 publications · 19 citations

    1

    h-index

  5. JA
    Janice A. Gifford

    Mount Holyoke College, United States

    1 publications · 103 citations

    1

    h-index

1–5 of 62

Venues

  1. Applied Psychological Measurement

    4 publications · 214 citations

    4

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  2. Geographical Analysis

    2 publications · 108 citations

    2

    h-index

  3. Educational and Psychological Measurement

    2 publications · 101 citations

    2

    h-index

  4. 2

    h-index

  5. 2

    h-index

1–5