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dc.contributor.authorGuo, Jingyi
dc.contributor.authorRiebler, Andrea Ingeborg
dc.description.abstractThis paper introduces the R package meta4diag for implementing Bayesian bivariate meta-analyses of diagnostic test studies. Our package meta4diag is a purpose-built front end of the R package INLA. While INLA offers full Bayesian inference for the large set of latent Gaussian models using integrated nested Laplace approximations, meta4diag 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 penalized complexity prior framework is supported, which builds on prior intuitions about the behaviors 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 summary receiver operating characteristic (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 R programming. The package is available from the Comprehensive R Archive Network (CRAN) at and its usage will be illustrated using three real data examples.nb_NO
dc.publisherFoundation for Open Access Statisticsnb_NO
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titlemeta4diag: Bayesian bivariate meta-analysis of diagnostic test studies for routine practicenb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.source.journalJournal of Statistical Softwarenb_NO
dc.relation.projectNorges forskningsråd: 240873nb_NO
dc.description.localcodeCreative Commons Attribution 3.0 Unported License.nb_NO
cristin.unitnameInstitutt for matematiske fag

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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal