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Diagnostic test accuracy: application and practice using R software

The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software w...

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Detalles Bibliográficos
Autores principales: Shim, Sung Ryul, Kim, Seong-Jang, Lee, Jonghoo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Korean Society of Epidemiology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6545496/
https://www.ncbi.nlm.nih.gov/pubmed/30999739
http://dx.doi.org/10.4178/epih.e2019007
Descripción
Sumario:The objective of this paper is to describe general approaches of diagnostic test accuracy (DTA) that are available for the quantitative synthesis of data using R software. We conduct a DTA that summarizes statistics for univariate analysis and bivariate analysis. The package commands of R software were “metaprop” and “metabin” for sensitivity, specificity, and diagnostic odds ratio; forest for forest plot; reitsma of “mada” for a summarized receiver-operating characteristic (ROC) curve; and “metareg” for meta-regression analysis. The estimated total effect sizes, test for heterogeneity and moderator effect, and a summarized ROC curve are reported using R software. In particular, we focus on how to calculate the effect sizes of target studies in DTA. This study focuses on the practical methods of DTA rather than theoretical concepts for researchers whose fields of study were non-statistics related. By performing this study, we hope that many researchers will use R software to determine the DTA more easily, and that there will be greater interest in related research.