Continuous ordinal regression for analysis of visual analogue scales: the R package ordinalCont

    Research output: Contribution to journalArticlepeer-review

    15 Citations (Scopus)
    126 Downloads (Pure)


    This paper introduces the R package ordinalCont, which implements an ordinal regression framework for response variables which are recorded on a visual analogue scale (VAS). This scale is used when recording subjects' perception of an intangible quantity such as pain, anxiety or quality of life, and consists of a mark made on a linear scale. We implement continuous ordinal regression models for VAS as the appropriate method of analysis for such responses, and introduce smoothing terms and random effects in the linear predictor. The model parameters are estimated using constrained optimization of the penalized likelihood and the penalty parameters are automatically selected via maximization of their marginal likelihood. The estimation algorithm is shown to perform well, in a simulation study. Two examples of application are given: the first involves the analysis of pain outcomes in a clinical trial for laser treatment for chronic neck pain; the second is an analysis of quality of life outcomes in a clinical trial for chemotherapy for the treatment of breast cancer.
    Original languageEnglish
    Pages (from-to)1-25
    Number of pages25
    JournalJournal of Statistical Software
    Issue number8
    Publication statusPublished - Nov 2020

    Bibliographical note

    Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


    • continuous ordinal regression
    • visual analogue scale
    • maximum penalized likelihood
    • splines
    • R


    Dive into the research topics of 'Continuous ordinal regression for analysis of visual analogue scales: the R package ordinalCont'. Together they form a unique fingerprint.

    Cite this