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ERIC Number: EJ1279706
Record Type: Journal
Publication Date: 2021-Jan
Pages: 10
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1759-2879
EISSN: N/A
IPDmada: An R Shiny Tool for Analyzing and Visualizing Individual Patient Data Meta-Analyses of Diagnostic Test Accuracy
Wang, Junfeng; Keusters, Willem R.; Wen, Lingzi; Leeflang, Mariska M. G.
Research Synthesis Methods, v12 n1 p45-54 Jan 2021
Background: Individual patient data meta-analyses (IPD-MA) are regarded as the gold standard for systematic reviews, which also applies to systematic reviews of diagnostic test accuracy (DTA) studies. An increasing number of DTA systematic reviews with IPD-MA have been published in recent years, but there is much variation in how these IPD-MA were performed. A number of existing methods were found, but there is no consensus as to which methods are preferred as the standard methods for statistical analysis in DTA IPD-MA. Objectives: To create a web-based tool which integrates recommended statistical analyses for DTA IPD-MA, and allows researchers to analyse the data and visualize the results with interactive plots. Methods: A systematic methodological review was performed to identify statistical analyses and data visualization methods used in DTA IPD-MA. Methods were evaluated by the authors and recommended analyses were integrated into the IPDmada tool which is freely available online with the user interface developed with R Shiny package. Results: IPDmada allows users to upload their own data, perform the meta-analysis with both continuous and dichotomized tests, and incorporate individual level covariate-adjusted analysis. All tables and figures can be exported as .csv or .pdf files. A hypothetical dataset was used to illustrate the application of IPDmada. Conclusions: IPDmada will be very helpful to researchers doing DTA IPD-MA, since it not only facilitates the statistical analysis but also provides a standard framework. The introduction of IPDmada will harmonize the methods used in DTA IPD-MA and ensure the quality of such analyses.
Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Publication Type: Journal Articles; Information Analyses
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A