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Qualitative method comparisons: examining a binary transformation

In this penultimate article in his series on method comparisons, Stephen MacDonald moves on from difference analysis and the contribution of Bland and Altman to consider qualitative methods and also the role of McNemar, Yates and Cohen.

The last three articles have been quite number heavy, with lots of graphs, as would be expected for investigation of quantitative assays. Qualitative assays are both similar and different. At their simplest, they categorise patients into normal/abnormal, diseased/non-diseased, positive/negative and a host of other binary classifications.

Classification is based on transforming a numerical measurement to a binary outcome based on a predetermined cut-off. Consequently, analysing method comparison studies is somewhat different from what we have seen in the last few articles. We are defining accuracy as how well the classifications agree. What form that classification takes (be it a condition accuracy – how well an assay can identify a disease process or not) or simply as an agreement between methods (when a disease state is not known) is dependent on the assay being compared.

Diagnostic accuracy comparisons involve testing our p

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