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Cited by 751

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

A unification of models for meta-analysis of diagnostic accuracy studies

Harbord, R. M., Deeks, J. J., Egger, M., Whiting, P., Sterne, J. A. C.·2007·Biostatistics

Abstract

Studies of diagnostic accuracy require more sophisticated methods for their meta-analysis than studies of therapeutic interventions. A number of different, and apparently divergent, methods for meta-analysis of diagnostic studies have been proposed, including two alternative approaches that are statistically rigorous and allow for between-study variability: the hierarchical summary receiver operating characteristic (ROC) model (Rutter and Gatsonis, 2001) and bivariate random-effects meta-analysis (van Houwelingen and others, 1993), (van Houwelingen and others, 2002), (Reitsma and others, 2005). We show that these two models are very closely related, and define the circumstances in which they are identical. We discuss the different forms of summary model output suggested by the two approaches, including summary ROC curves, summary points, confidence regions, and prediction regions.

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Metadata

Authors
Harbord, R. M., Deeks, J. J., Egger, M., Whiting, P., & Sterne, J. A. C.
Venue
Biostatistics
Published
2006-05-11
Volume
8
Issue
2
Pages
239-251
ISSN
  • 1465-4644 (ISSN-L)
  • 1468-4357
OpenAlex
W2116308061
Cited by
751
References
6
FWCI
8.30
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A unification of models for meta-analysis of diagnostic accuracy studies. https://app.cochat.ai/papers/10.1093/biostatistics/kxl004
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Harbord, R. M., Deeks, J. J., Egger, M., Whiting, P., & Sterne, J. A. C. (2007). A unification of models for meta-analysis of diagnostic accuracy studies. Biostatistics. https://doi.org/10.1093/biostatistics/kxl004

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.