Using the R Software to Conduct Network Meta-Analysis on Diabetes Data” h

Year : 2024 | Volume : 13 | Issue : 02 | Page : 57 76
    By

    Nilgün Yildiz,

  1. Associate Professor, Marmara University Göztepe Campus, University in Istanbul, Istanbul, Turkey

Abstract

A meta-analysis’s goal is typically to quantify the total treatment effect and draw conclusions regarding the differences in effects between the two treatments. Meta-analysis is a quantitative method for combining the findings of several studies in the social and medical sciences.. A meta-analysis might be of three typical forms. Network-wide, pairwise, and multivariate meta-analyses are all possible. The integrated assessment of more than two treatments is generally made possible by network meta-analysis (NMA). Mainly, frequentist and Bayesian frameworks are used to categorize statistical methods to NMA. Because a portion of NMA includes indirect, repeated comparisons, As network meta-analyses grow more popular, it is critical to introduce the method to readers and provide information on how to interpret the results. This chapter defines words used in network mental analysis (NMA), provides an overview of pertinent statistical concepts, and uses an example of a network containing Diabetes treatments and the R program to demonstrate the NMA analytic method based on the frequentist and bayesian framework. The article’s goal is to compare the fundamental ideas and analyses of network meta-analysis with diabetes data and employed treatment approaches.

Keywords: Network meta-analysis (NMA), diabetes treatment, R software, frequentist and Bayesian frameworks, statistical methods in meta-analysis

[This article belongs to Research & Reviews : Journal of Statistics ]

How to cite this article:
Nilgün Yildiz. Using the R Software to Conduct Network Meta-Analysis on Diabetes Data” h. Research & Reviews : Journal of Statistics. 2024; 13(02):57-76.
How to cite this URL:
Nilgün Yildiz. Using the R Software to Conduct Network Meta-Analysis on Diabetes Data” h. Research & Reviews : Journal of Statistics. 2024; 13(02):57-76. Available from: https://journals.stmjournals.com/rrjost/article=2024/view=203186


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Regular Issue Subscription Review Article
Volume 13
Issue 02
Received 07/08/2024
Accepted 15/08/2024
Published 20/08/2024
Publication Time 13 Days
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