A case study of an individual participant data meta-analysis of diagnostic accuracy showed that prediction regions represented heterogeneity well.

ABSTRACT: The diagnostic accuracy of a screening tool is often characterized by its sensitivity and specificity. An analysis of these measures must consider their intrinsic correlation. In the context of an individual participant data meta-analysis, heterogeneity is one of the main components of the analysis. When using a random-effects meta-analytic model, prediction regions provide deeper insight into the effect of heterogeneity on the variability of estimated accuracy measures across the entire studied population, not just the average. This study aimed to investigate heterogeneity via prediction regions in an individual participant data meta-analysis of the sensitivity and specificity of the Patient Health Questionnaire-9 for screening to detect major depression. From the total number of studies

SUBMITTER: de Lara ALMV 

PROVIDER: S-EPMC10247712 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature