IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0121760.html
   My bibliography  Save this article

medplot: A Web Application for Dynamic Summary and Analysis of Longitudinal Medical Data Based on R

Author

Listed:
  • Črt Ahlin
  • Daša Stupica
  • Franc Strle
  • Lara Lusa

Abstract

In biomedical studies the patients are often evaluated numerous times and a large number of variables are recorded at each time-point. Data entry and manipulation of longitudinal data can be performed using spreadsheet programs, which usually include some data plotting and analysis capabilities and are straightforward to use, but are not designed for the analyses of complex longitudinal data. Specialized statistical software offers more flexibility and capabilities, but first time users with biomedical background often find its use difficult. We developed medplot, an interactive web application that simplifies the exploration and analysis of longitudinal data. The application can be used to summarize, visualize and analyze data by researchers that are not familiar with statistical programs and whose knowledge of statistics is limited. The summary tools produce publication-ready tables and graphs. The analysis tools include features that are seldom available in spreadsheet software, such as correction for multiple testing, repeated measurement analyses and flexible non-linear modeling of the association of the numerical variables with the outcome. medplot is freely available and open source, it has an intuitive graphical user interface (GUI), it is accessible via the Internet and can be used within a web browser, without the need for installing and maintaining programs locally on the user’s computer. This paper describes the application and gives detailed examples describing how to use the application on real data from a clinical study including patients with early Lyme borreliosis.

Suggested Citation

  • Črt Ahlin & Daša Stupica & Franc Strle & Lara Lusa, 2015. "medplot: A Web Application for Dynamic Summary and Analysis of Longitudinal Medical Data Based on R," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-19, April.
  • Handle: RePEc:plo:pone00:0121760
    DOI: 10.1371/journal.pone.0121760
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0121760
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0121760&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0121760?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
    ---><---

    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:plo:pone00:0121760. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.