Residual Deviance Analysis

Residual Deviance Analysis is a statistical assessment method that evaluates the discrepancy between observed categorical data and a fitted model by measuring the deviance contribution of individual residuals to determine the adequacy of model fit.

42

Publications

2.8K

Citations

95

Authors

47

Institutions

Publications per year

2017–2026

6

Authors

95

  1. AE
    A. E. Ades

    University of Bristol, United Kingdom

    3 publications · 144 citations

    3

    h-index

  2. NJ
    Nicky J. Welton

    University of Bristol, United Kingdom

    3 publications · 144 citations

    3

    h-index

  3. DC
    Douglas C. Montgomery

    Arizona State University, United States

    2 publications · 126 citations

    2

    h-index

  4. DJ
    Duangporn Jearkpaporn

    Arizona State University, United States

    2 publications · 126 citations

    2

    h-index

  5. WC
    Wing-Shing Chan

    Michigan State University, United States

    2 publications · 235 citations

    2

    h-index

1–5 of 95

Venues

  1. Statistics in Medicine

    3 publications · 192 citations

    3

    h-index

  2. Biometrika

    2 publications · 61 citations

    2

    h-index

  3. 2

    h-index

  4. Journal of Consulting and Clinical Psychology

    2 publications · 235 citations

    2

    h-index

  5. Journal of Vegetation Science

    JVS · 1 publications · 23 citations

    1

    h-index

1–5