  Introduction: Despite their applicability, statistical models used for the
meta-analysis of test accuracy require specialised knowledge to implement, with
the necessary level of expertise having recently increased. This is due to the
development and recommendation to use more sophisticated methods; such as those
in Version 2 of the Cochrane Handbook for Systematic Reviews of Diagnostic Test
Accuracy. This paper describes a web-based application that extends the
functionality of previous applications, making many advanced analysis methods
more accessible.
  Methods: We sought to create an extended, stand-alone, Bayesian version of
MetaDTA, which (i) has the benefits of previously proposed applications and
addresses key limitations of them, (ii) is accessible to researchers who do not
have the specific expertise required to fit such models, and (iii) is suitable
for experienced analysts. We created the application using Shiny and Stan.
  Results: We created MetaBayesDTA (https://crsu.shinyapps.io/MetaBayesDTA/),
which allows users to conduct meta-analysis of test accuracy, with or without a
gold standard. The application addresses several key limitations of other
applications. For instance, for the bivariate model, one can conduct subgroup
analysis, univariate meta-regression, and comparative test accuracy evaluation.
Meanwhile, for the model which does not assume a perfect gold standard, the
application can account for the fact that studies use different reference
tests.
  Conclusions: Due to its user-friendliness and broad array of features,
MetaBayesDTA should appeal to a wide variety of researchers. We anticipate that
the application will encourage wider use of more advanced methods, which
ultimately should improve the quality of test accuracy reviews.
