Model Parsimony

Model Parsimony is a principle in model building that favors simpler models over more complex ones when they explain the data equally well, distinguished by its adherence to the criterion of minimizing unnecessary structural or parametric complexity while maintaining explanatory power.

162

Publications

21.1K

Citations

371

Authors

249

Institutions

Publications per year

2017–2026

35

Variants

Principle Of Parsimony

Authors

371

  1. ES
    Elliott Sober

    University of Wisconsin–Madison, United States

    4 publications · 208 citations

    4

    h-index

  2. KJ
    Kristopher J. Preacher

    Vanderbilt University, United States

    2 publications · 195 citations

    2

    h-index

  3. JC
    John C. Avise

    University of Georgia, United States

    2 publications · 56 citations

    2

    h-index

  4. RK
    Robert Kohn

    UNSW Sydney, Australia

    2 publications · 76 citations

    2

    h-index

  5. HW
    Herbert W. Marsh

    Western Sydney University, Australia

    2 publications · 903 citations

    2

    h-index

1–5 of 371

Venues

  1. Cladistics

    9 publications · 649 citations

    9

    h-index

  2. The Journal of Experimental Education

    3 publications · 756 citations

    3

    h-index

  3. Systematic Biology

    3 publications · 124 citations

    3

    h-index

  4. Evolution

    2 publications · 56 citations

    2

    h-index

  5. Psychological Bulletin

    2 publications · 487 citations

    2

    h-index

1–5