Dependent Item Response Models

Dependent Item Response Models is a class of psychometric models that extends traditional item response theory by incorporating local item dependencies through structured latent variables or residual correlations, thereby accounting for response patterns that violate the assumption of conditional independence.

65

Publications

3.6K

Citations

125

Authors

69

Institutions

Publications per year

2017–2026

13

Variants

Dependent IrmDependent Irt Models

Authors

125

  1. DM
    Daniel M. Bolt

    University of Wisconsin–Madison, United States

    4 publications · 363 citations

    4

    h-index

  2. PD
    Paul De Boeck

    KU Leuven, Belgium

    3 publications · 394 citations

    4

    h-index

  3. FT
    Francis Tuerlinckx

    KU Leuven, Belgium

    2 publications · 318 citations

    3

    h-index

  4. HO
    Haruhiko Ogasawara

    Otaru University of Commerce, Japan

    3 publications · 55 citations

    3

    h-index

  5. ET
    Eric T. Bradlow

    University of Pennsylvania, United States

    3 publications · 284 citations

    3

    h-index

1–5 of 125

Venues

  1. Psychometrika

    14 publications · 1.1K citations

    14

    h-index

  2. Applied Psychological Measurement

    8 publications · 377 citations

    8

    h-index

  3. 3

    h-index

  4. 2

    h-index

  5. ETS Research Report Series

    2 publications · 154 citations

    2

    h-index

1–5