2015/12/19 by Jingyi Guo, Guo, Jingyi, Andrea Riebler +1
Decision Sciences · Mathematics · #Applications (stat.AP) #FOS: Computer and information sciences #Meta-analysis and systematic reviews #Methodology (stat.ME) #Statistical Methods and Bayesian Inference #Statistical Methods in Clinical Trials
paper · pdf · doi:10.48550/arxiv.1512.06220
openalex publication_date 2015/12/19 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
This paper introduces the \proglangR package \pkgmeta4diag for implementing Bayesian bivariate meta-analyses of diagnostic test studies. Our package \pkgmeta4diag is a purpose-built front end of the \proglangR package \pkgINLA. While \pkgINLA offers full Bayesian inference for the large set of latent Gaussian models using integrated nested Laplace approximations, \pkgmeta4diag extracts the features needed for bivariate meta-analysis and presents them in an intuitive way. It allows the user a straightforward model-specification and offers user-specific prior distributions. Further, the newly proposed penalised complexity prior framework is supported, which builds on prior intuitions about the behaviours of the variance and correlation parameters. Accurate posterior marginal distributions for sensitivity and specificity as well as all hyperparameters, and covariates are directly obtained without Markov chain Monte Carlo sampling. Further, univariate estimates of interest, such as odds ratios, as well as the SROC curve and other common graphics are directly available for interpretation. An interactive graphical user interface provides the user with the full functionality of the package without requiring any \proglangR programming. The package is available through CRAN \urlhttps://cran.r-project.org/web/packages/meta4diag/ and its usage will be illustrated using three real data examples.