Regression Interpretation

Regression Interpretation is a statistical method that identifies and quantifies the relationship between a dependent variable and one or more independent variables by estimating the magnitude, direction, and significance of predictive effects within a regression model.

42

Publications

3.5K

Citations

68

Authors

50

Institutions

Publications per year

2017–2026

8

Authors

68

  1. RC
    Ronald C. Serlin

    University of Wisconsin–Madison, United States

    2 publications · 40 citations

    2

    h-index

  2. EF
    Edwin F. Ulveling

    Georgia State University, United States

    2 publications · 72 citations

    2

    h-index

  3. RE
    Robert E. Sweeney

    Icahn School of Medicine at Mount Sinai, United States

    2 publications · 72 citations

    2

    h-index

  4. JZ
    Ji Zhu

    University of Michigan, United States

    2 publications · 402 citations

    2

    h-index

  5. JR
    Joel R. Levin

    University of Wisconsin–Madison, United States

    2 publications · 40 citations

    2

    h-index

1–5 of 68

Venues

  1. The American Statistician

    6 publications · 418 citations

    6

    h-index

  2. Sociological Methods & Research

    SMR · 3 publications · 110 citations

    3

    h-index

  3. Journal of Educational Statistics

    2 publications · 40 citations

    2

    h-index

  4. 2

    h-index

  5. The Review of Economics and Statistics

    1 publications · 253 citations

    1

    h-index

1–5