Revisiting Youden’s index as a useful measure of the misclassification error in meta-analysis of diagnostic studies
Böhning, Dankmar, Böhning, Walailuck and Holling, Heinz (2008) Revisiting Youden’s index as a useful measure of the misclassification error in meta-analysis of diagnostic studies. Statistical Methods in Medical Research, 17, (6), 543-554. (doi:10.1177/0962280207081867). (PMID:18375457).
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The paper considers meta-analysis of diagnostic studies that use a continuous score for classification of study participants into healthy or diseased groups. Classification is often done on the basis of a threshold or cut-off value, which might vary between studies. Consequently, conventional meta-analysis methodology focusing solely on separate analysis of sensitivity and specificity might be confounded by a potentially unknown variation of the cut-off value. To cope with this phenomena it is suggested to use, instead, an overall estimate of the misclassification error previously suggested and used as Youden's index and; furthermore, it is argued that this index is less prone to between-study variation of cut-off values. A simple Mantel—Haenszel estimator as a summary measure of the overall misclassification error is suggested, which adjusts for a potential study effect. The measure of the misclassification error based on Youden's index is advantageous in that it easily allows an extension to a likelihood approach, which is then able to cope with unobserved heterogeneity via a nonparametric mixture model. All methods are illustrated at hand of an example on a diagnostic meta-analysis on duplex doppler ultrasound, with angiography as the standard for stroke prevention
|Digital Object Identifier (DOI):||doi:10.1177/0962280207081867|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||Faculty of Social and Human Sciences > Mathematical Sciences > Statistics
Faculty of Social and Human Sciences > Southampton Statistical Sciences Research Institute
|Date Deposited:||09 Feb 2012 12:00|
|Last Modified:||31 Mar 2016 13:49|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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