Robust statistical methods in R using the WRS2 package

  title={Robust statistical methods in R using the WRS2 package},
  author={P. Mair and R. Wilcox},
  journal={Behavior Research Methods},
  • P. Mair, R. Wilcox
  • Published 2019
  • Computer Science, Medicine
  • Behavior Research Methods
  • This paper introduces the R package WRS2 that implements various robust statistical methods. It elaborates on the basics of robust statistics by introducing robust location, dispersion, and correlation measures. The location and dispersion measures are then used in robust variants of independent and dependent samples t tests and ANOVA, including between-within subject designs and quantile ANOVA. Further, robust ANCOVA as well as robust mediation models are introduced. The paper targets applied… CONTINUE READING
    111 Citations

    Figures and Topics from this paper

    Age and Sex Differences in Morningness/Eveningness Along the Life Span: A Cross-Sectional Study in Spain
    • 12
    The organizational principles of de-differentiated topographic maps
    • 1
    • PDF
    An experimental evaluation of a de-biasing intervention for professional software developers
    • 7
    • PDF
    A Translational Paradigm to Study the Effects of Uncontrollable Stress in Humans
    • PDF
    Robustness of Deep Learning Methods for Ocular Fundus Segmentation: Evaluation of Blur Sensitivity
    • V. Petrovic, Gorana Gojić, +4 authors Ana Oros
    • Computer Science
    • 2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA)
    • 2020


    Robust statistical methods: A primer for clinical psychology and experimental psychopathology researchers.
    • 110
    • PDF
    Beyond differences in means: robust graphical methods to compare two groups in neuroscience
    • 71
    • PDF
    Use of Ranks in One-Criterion Variance Analysis
    • 7,068
    • PDF
    Functional Data Analysis
    • 1,522