DTA Meta-Analysis

Diagnostic Test Accuracy (DTA) Meta-Analysis involves aggregating estimates of sensitivity and specificity across studies using a bivariate meta-analysis model. Two models are commonly recognized in the literature: 1) the bivariate meta-analysis model, 2) the hierarchical summary receiver-operating-characteristic (HSROC) curve model. More about these models can be found in the Cochrane Handbook for DTA Meta-Analysis.

Shiny App

The Bayesian DTA Meta-Analysis Shiny App provides an easy-to-use interface to implement a Bayesian bivariate meta-analysis model with or without a perfect reference test.

Peer-reviewed articles

The following articles illustrate use of DTA meta-analysis models.

When the reference test is assumed to be perfect

When verification bias is present

When the reference test is assumed to be imperfect (Latent class meta-analysis)