The metacor, which is developed based on the classical frequentist theory, is a specified package for performing meta-analysis of correlation coefficients in R software. This package was officially launched in 2011. Based on the DerSimonian-Laird method and Olkin-Pratt method, correlation coefficients can be directly pooled by using this package. The metacor package also can be used to draw the forest plot and is easy to use; however, it still needs to be improved. This paper briefly introduced how to perform a meta-analysis of correlation coefficients using the metacor package in R software through an example.
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.
R software is a free and powerful statistical tool, including Metafor, Meta as well as Rmeta packages, all of which could conduct meta-analysis. Metafor package provides functions for meta-analyses which include analysis of continuous and categorical data, meta-regression, cumulative meta-analysis as well as test for funnel plot asymmetry. The package can also draw various plots, such as forest plot, funnel plot, radial plot and so forth. Mixed-effects models (involving single or multiple categorical and/or continuous moderates) can only be fitted with Metafor packages. Advanced methods for testing model coefficients and confidence intervals are also implemented only in this package. This article introduces detailed operation steps of Metafor package for meta-analysis using cases.
The theoretical foundation of relevant packages of R software for network meta-analysis is mainly based on Bayesian statistical model and a few of them use generalized linear model. Network meta-analysis is performed using GeMTC R package through calling the corresponding rjags package, BRugs package, or R2WinBUGS package (namely, JAGS, OpenBUGS, and WinBUGS software, respectively). Meanwhile, GeMTC R package can generate data storage files for GeMTC software. Techonically, network meta-analysis is performed through calling the software based on Markov Chain Monte Carlo method. In this article, we briefly introduce how to use GeMTC R package to perform network meta-analysis through calling the OpenBUGS software.
The mada package is a type of package that is especially used for implementing meta-analysis of diagnostic accuracy tests. This package is developed on basis of classical statistical theories and it can be used to calculate all relevant effect size of diagnostic accuracy tests; however, it does not provide pooled values of sensitivity and specificity. This article uses an example to introduce the whole functions of mada package in implementing meta-analysis of diagnostic accuracy tests, including data preparation, calculation implementation, result summary, and plots drawing.
The published methodological studies about network meta-analysis mostly focused on the binary variables, but study focused on the continuous variables was few. This study introduces how to use R, GeMTC and Stata softwares jointly to produce various graphics of continuous variable network meta-analysis. It also introduces how to perform the convergence diagnostics, trace and density plot, forest, rank probabilities and rankogram, internal relationship summary chart, network plot, contribution plot and publication bias test.
The association between single nucleotide polymorphism and disease is a typical representation of genetic association studies. Compared with the traditional dichotomous data, single nucleotide polymorphism data has its own characteristics, and 5 genetic models are commonly performed in meta-analysis. In this paper, we show how to use the " meta” package in R software to conduct meta-analysis of single nucleotide polymorphism research through examples.
R software is a free, powerful statistical and graphing software, including metafor, meta as well as metaplus packages. They can be used to conduct meta-analysis. This article introduces detailed operations of the metaplus package for meta-analysis using cases.
The method of network meta-analysis of diagnostic test accuracy is in the exploratory stage. We had explored and introduced several methods of network meta-analysis of diagnostic test accuracy before. Based on example, we introduce ANOVA model for performing network meta-analysis of diagnostic test accuracy step-by-step.
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.