Bayesian Multidimensional Scaling

Bayesian Multidimensional Scaling is a statistical modeling framework within Bayesian Item Response Theory that extends classical multidimensional scaling by incorporating Bayesian inference to estimate latent trait dimensions while accounting for parameter uncertainty through posterior distributions.

17

Publications

516

Citations

44

Authors

23

Institutions

Publications per year

2017–2026

3

Authors

44

  1. WS
    Wayne S. DeSarbo

    Pennsylvania State University, United States

    3 publications · 68 citations

    3

    h-index

  2. DΚ
    Duncan Κ. H. Fong

    Pennsylvania State University, United States

    3 publications · 63 citations

    3

    h-index

  3. RB
    Ryan Bakker

    University of Georgia, United States

    2 publications · 47 citations

    2

    h-index

  4. KO
    Kensuke Okada

    Senshu University, Japan

    2 publications · 36 citations

    2

    h-index

  5. KT
    Keith T. Poole

    University of Georgia, United States

    2 publications · 47 citations

    2

    h-index

1–5 of 44

Venues

  1. 2

    h-index

  2. Psychometrika

    1 publications · 19 citations

    1

    h-index

  3. Behavior Research Methods

    BRM · 1 publications · 14 citations

    1

    h-index

  4. IEEE/CAA Journal of Automatica Sinica

    1 publications · 30 citations

    1

    h-index

  5. Current Biology

    1 publications · 59 citations

    1

    h-index

1–5