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find Keyword "WinBUGS software" 3 results
  • Implementation of Network Meta-Analysis Using Stata Software

    The WinBUGS software can be called from either R (provided R2WinBUGS as an R package) or Stata software for network meta-analysis. Unlike R, Stata software needs to create relevant ADO scripts at first which simplify operation process greatly. Similar with R, Stata software also needs to load another package when drawing network plots. This article briefly introduces how to implement network meta-analysis using Stata software by calling WinBUGS software.

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  • Application of R2WinBUGS Package of R Software for Network Meta-Analysis

    R Software is an open, free of use and charge statistical software which has a powerful graphic capability; however, it requires more complex codes and commands to perform network meta-analysis, which causes errors and difficulties in operation. WinBUGS software is based on Bayesian theory, which has a powerful data processing capability, and especially its codes are simple and easy to operate for dealing with network meta-analysis. However, its function of illustrating statistical results is very poor. In order to fully integrate the advantages of R software and WinBUGS software, an R2WinBUGS package based on R software has been developed which builds a “bridge” across two of them, making network meta-analysis process conveniently, quickly and result illustration more beautiful. In this article, we introduced how to use the R2WinBUGS package for performing network meta-analysis using examples.

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  • Constructing the Doodle for Performing Meta-analysis in WinBUGS Software

    The key for performing meta-analysis using WinBUGS software is to construct a model of Bayesian statistics. The hand-written code model and Doodle model are two major methods for constructing it. The approach of hand-written code is flexible and convenient, but the language programming is fallibility. The Doodle is complicated, but it is benefit to understand the structure of hand-written code model and prevent error. This article briefly describes how to construct the Doodle model for binary and continuous data of head to head meta-analysis, indirect comparison and network meta-analysis, and ordinal variables meta-analysis.

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