Robust Analysis Of Variance

Robust Analysis of Variance is a statistical method that belongs to the class of analysis of variance techniques, distinguished by its ability to provide valid inferences under violations of standard assumptions such as normality, homoscedasticity, and the presence of outliers through the incorporation of robust estimation and weighting procedures.

444

Publications

46.6K

Citations

1.5K

Authors

684

Institutions

Publications per year

2017–2026

180

Variants

Robust Anova

Authors

1.5K

  1. RR
    Rand R. Wilcox

    University of Southern California, United States

    12 publications · 2.9K citations

    12

    h-index

  2. AB
    Alan B. Forsythe

    University of California, Los Angeles, United States

    7 publications · 4.5K citations

    7

    h-index

  3. CL
    Chandra L. Jackson

    National Institute of Environmental Health Sciences, United States

    6 publications · 379 citations

    6

    h-index

  4. AE
    Albert Espelt

    Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública, Spain

    6 publications · 186 citations

    6

    h-index

  5. ET
    Elizabeth Tipton

    Columbia University, United States

    6 publications · 1.4K citations

    6

    h-index

1–5 of 1.5K

Venues

  1. Technometrics

    23 publications · 4K citations

    20

    h-index

  2. Journal of the American Statistical Association

    17 publications · 5.3K citations

    17

    h-index

  3. Biometrics

    14 publications · 3.9K citations

    14

    h-index

  4. PLoS ONE

    13 publications · 1.1K citations

    13

    h-index

  5. Revista de Saúde Pública

    RSP · 12 publications · 432 citations

    12

    h-index

1–5