Log-log Regression

Log-Log Regression is a regression analysis method in which both the dependent and independent variables are transformed using logarithms to model a power-law relationship between variables, enabling the estimation of proportional changes in one variable relative to another on a logarithmic scale.

424

Publications

30.3K

Citations

1.4K

Authors

560

Institutions

Publications per year

2017–2026

71

Variants

Log-log Model

Authors

1.4K

  1. GM
    G. M. Hughes

    University of Bristol, United Kingdom

    4 publications · 103 citations

    4

    h-index

  2. ST
    Silvana Tenreyro

    London School of Economics and Political Science, United Kingdom

    3 publications · 6.3K citations

    3

    h-index

  3. PW
    Paul W. Davenport

    University of Florida, United States

    3 publications · 174 citations

    3

    h-index

  4. IL
    Isaac Luginaah

    Western University, Canada

    3 publications · 93 citations

    3

    h-index

  5. DK
    David K. Hildebrand

    University of Pennsylvania, United States

    2 publications · 41 citations

    2

    h-index

1–5 of 1.4K

Venues

  1. PubMed

    Repository · 8 publications · 467 citations

    8

    h-index

  2. Journal of Applied Physiology

    7 publications · 1K citations

    7

    h-index

  3. Medicine & Science in Sports & Exercise

    MSSE · 5 publications · 435 citations

    5

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 5 publications · 205 citations

    5

    h-index

  5. American Journal of Public Health

    JPH · 5 publications · 749 citations

    5

    h-index

1–5