Aggregating multiple test results to improve medical decision-making
Fig 5
ROC curves associated with the aggregation of three antigen tests (Abbot, Innova, and Siemens).
The sensitivities and specificities of the n = 3 tests are listed in Table 2. (A) The ROC curve associated with the aggregation of the three antigen tests as derived from Eqs (33) and (35). We use Yi ∈ {0, 1} to denote the outcome of test i ∈ {1, 2, 3}. The dashed curve is a visual guide connecting the tests on the ROC curve. (B) A magnified view of the ROC curve without the trivial combined tests that classify all samples as either negative or positive. The error bars indicate the 95% CIs that we generated from 106 samples of beta distributions capturing the 95% CIs of the underlying individual sensitivities and specificities.