Residual Correlation Analysis

Residual Correlation Analysis is a statistical method used in dimensionality assessment that evaluates the discrepancy between observed and model-implied correlation matrices to identify misfit and potential omitted dimensions in psychometric or factor models.

108

Publications

10K

Citations

351

Authors

199

Institutions

Publications per year

2017–2026

21

Authors

351

  1. FS
    Fiona Steele

    University of Bristol, United Kingdom

    5 publications · 282 citations

    5

    h-index

  2. GG
    Gabriele Gradoni

    University of Nottingham, United Kingdom

    2 publications · 68 citations

    2

    h-index

  3. DM
    David M. Evans

    University of Bristol, United Kingdom

    2 publications · 189 citations

    2

    h-index

  4. JG
    Jeff Goldsmith

    Columbia University, United States

    2 publications · 85 citations

    2

    h-index

  5. CH
    Chêng Hsiao

    University of Southern California, United States

    2 publications · 64 citations

    2

    h-index

1–5 of 351

Venues

  1. The Journal of Chemical Physics

    3 publications · 141 citations

    3

    h-index

  2. 3

    h-index

  3. Structural Equation Modeling A Multidisciplinary Journal

    SEM · 3 publications · 186 citations

    3

    h-index

  4. Genetic Epidemiology

    3 publications · 145 citations

    3

    h-index

  5. Journal of Business and Economic Statistics

    JBES · 2 publications · 80 citations

    2

    h-index

1–5