English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Meta-analysis for diagnostic test accuracy (DTA) has been a standard researchmethod for synthesizing evidence from diagnostic studies. In DTA meta-analysis,although publication bias is an important source of bias, no certain methodssimilar to the Egger test in univariate meta-analysis have been developed todetect such bias. However, several recent studies have discussed these methodsin the framework of multivariate meta-analysis, and some generalized Eggertests have been developed. The R package MVPBT(https://cran.r-project.org/web/packages/MVPBT/) was developed to implement thegeneralized Egger tests developed by Noma (2020; Biometrics 76, 1255-1259) forDTA meta-analysis. Noma's publication bias tests effectively incorporate thecorrelation information between multiple outcomes and are expected to improvethe statistical powers. The present paper provides a nontechnical introductionand practical examples of data analyses of the publication bias tests of DTAmeta-analysis using the MVPBT package.

MVPBT: R package for publication bias tests in meta-analysis of diagnostic accuracy studies