IDEAS home Printed from https://ideas.repec.org/a/taf/amstat/v68y2014i2p98-103.html
   My bibliography  Save this article

A Decorated Parallel Coordinate Plot for Categorical Longitudinal Data

Author

Listed:
  • Reto Bürgin
  • Gilbert Ritschard

Abstract

This article proposes a decorated parallel coordinate plot for longitudinal categorical data, featuring a jitter mechanism revealing the diversity of observed longitudinal patterns and allowing the tracking of each individual pattern, variable point and line widths reflecting weighted pattern frequencies, the rendering of simultaneous events, and different filter options for highlighting typical patterns. The proposed visual display has been developed for describing and exploring the order of event occurrences, but it can be equally applied to other types of longitudinal categorical data. Alongside the description of the principle of the plot, we demonstrate the scope of the plot with a real dataset. A second application and R code for the plot are available online as supplementary materials.

Suggested Citation

  • Reto Bürgin & Gilbert Ritschard, 2014. "A Decorated Parallel Coordinate Plot for Categorical Longitudinal Data," The American Statistician, Taylor & Francis Journals, vol. 68(2), pages 98-103, May.
    • Handle: RePEc:taf:amstat:v:68:y:2014:i:2:p:98-103
    DOI: 10.1080/00031305.2014.887591
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/00031305.2014.887591
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/00031305.2014.887591?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cees H. Elzinga & Matthias Studer, 2015. "Spell Sequences, State Proximities, and Distance Metrics," Sociological Methods & Research, , vol. 44(1), pages 3-47, February.
    2. Liao, Tim F. & Bolano, Danilo & Brzinsky-Fay, Christian & Cornwell, Benjamin & Fasang, Anette Eva & Helske, Satu & Piccarreta, Raffaella & Raab, Marcel & Ritschard, Gilbert & Struffolino, Emanuela & S, 2022. "Sequence analysis: Its past, present, and future," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 107, pages 1-1.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:amstat:v:68:y:2014:i:2:p:98-103. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/UTAS20 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.