IDEAS home Printed from https://ideas.repec.org/h/ito/pchaps/242205.html
   My bibliography  Save this book chapter

Network Meta-Analysis Using R for Diabetes Data

In: Computational Statistics and Applications

Author

Listed:
  • Nilgun Yildiz

Abstract

The objective of a meta-analysis is usually to estimate the overall treatment effect and make inferences about the difference between the effects of the two treatments. Meta-analysis is a quantitative method commonly used to combine the results of multiple studies in the medical and social sciences. There are three common types of meta-analysis. Pairwise, Multivariate and Network Meta-analysis. In general, network meta-analysis (NMA) offers the advantage of enabling the combined assessment of more than two treatments. Statistical approaches to NMA are largely classified as frequentist and Bayesian frameworks Because part of NMA has indirect, multiple comparisons, As reports of network meta-analysis become more common, it is essential to introduce the approach to readers and to provide guidance as to how to interpret the results. In this chapter, the terms used in NMA are defined, relevant statistical concepts are summarized, and the NMA analytic process based on the frequentist and Bayesian framework is illustrated using the R program and an example of a network involving diabetes treatments. The aim of the article is to compare the basic concepts and analyzes of network meta-analysis using diabetes data and the treatment methods used.

Suggested Citation

  • Nilgun Yildiz, 2022. "Network Meta-Analysis Using R for Diabetes Data," Chapters, in: Ricardo Lopez-Ruiz (ed.), Computational Statistics and Applications, IntechOpen.
    • Handle: RePEc:ito:pchaps:242205
    DOI: 10.5772/intechopen.101788
    as

    Download full text from publisher

    File URL: https://www.intechopen.com/chapters/80086
    Download Restriction: no
    File URL: https://libkey.io/10.5772/intechopen.101788?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

    Keywords

    Network meta-analysis; fixed effect model; random-effects model; forest plot; network graph; direct evidence plot;
    All these keywords.

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General

    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:ito:pchaps:242205. 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: Slobodan Momcilovic (email available below). General contact details of provider: http://www.intechopen.com .

    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.