ObjectiveTo compare the characteristics and functions of the network meta-analysis software and for providing references for users. MethodsPubMed, CNKI, official website of Stata and R, and Google were searched to collect the software and packages that can perform network meta-analysis up to July 2014. After downloading the software, packages, and their user guides, we used the software and packages to calculate a typical example. The characteristics, functions, and computed results were compared and analyzed. ResultsFinally, 11 types of software were included, including programming and non-programming software. They were developed mainly based on Bayesian or Frequentist. Most types of software have the characteristics of easy to operate, easy to master, exactitude calculation, or good graphing; however, there is no software that has the exactitude calculation and good graphing at the same time, which needs two or more kinds of software combined to achieve. ConclusionWe suggest the user to choose the software at least according to personal programming basis and custom; and the user can consider to choose two or more kinds of software combined to finish the objective network meta-analysis. We also suggest to develop a kind of software which is characterized of fully function, easy operation, and free.
The goal of JAGS (Just Another Gibbs Sampler) software is to remedy the short of BUGS software that unable to running on a system besides Microsoft Windows, such as Unix or Linux. JAGS owns independent computing function and formula of Bayesian theory; it is mischaracterized with simple user interface, good system compatibility, smoother operation, and good interactivity with other programming software. However, due to the limitations of lacking function for results data reading and unscrambling and graph plotting, the popularization and application of JAGS software is restricted. Calling JAGS software from R software through R2jags package, rjags package, or runjags package can overcome these limitations. The operating principle of these three packages is calling JAGS software in the framework of the R software, they have similar functional structure and all have easy maneuverability, concise command, perfect function of data reading and unscrambling and graph drawing; however, there are some differences among them in practice. This article introduces how to performing network meta-analysis by calling JAGS software from R through these three packages.
The pcnetmeta package in R is a special package for performing network meta-analysis based on Bayesian theory, which combines the strength computing function of JAGS software and the special data integration and powerful graph drawing function of R software. This package conducts calculation by calling JAGS, provides 3 different models for users, and each model can yield results of 3 effect-sizes (RR, OR and RD). At the same time, this package can draw many kinds of plots, which greatly meets actual needs of users to deal with complicated network meta-analysis. In this article, we introduce how to use pcnetmeta package to perform network meta-analysis based on an example.