Comparing the sensitivity and specificity two diagnostic tests

Compare the sensitivity and specificity of two diagnostic tests and make inferences about the differences.

1. Select a cell in the dataset.
2. On the Analyse-it ribbon tab, in the Statistical Analyses group, click Diagnostic, and then click Binary (Sensitivity / Specificity).
   The analysis task pane opens.
3. In the Model drop-down menu, select the number of tests and the type of study design.

   Option	Description
   2 paired tests	Compare 2 tests where the results are on the same subjects.
   2 independent tests / groups	Compare 2 tests where the results are on different subjects, or 1 test applied to 2 different groups of subjects.

4. In the True state drop-down list, select the true condition variable.
5. In the Positive event drop-down list, select the state that indicates the presence of the condition/event of interest.
6. If comparing 2 independent tests, in the Y drop-down list, select the diagnostic test variable, and then in the Factor drop-down list, select the factor variable (test or group indicator).
7. If comparing 2 paired tests, in the Y drop-down lists, select the diagnostic test variables.
8. If the data are in frequency form, in the Frequency drop-down list, select the frequency count variable.
9. On the Analyse-it ribbon tab, in the Diagnostic Accuracy group, click Test, and then click:

   Option	Description
   Equality	Test if the sensitivities/specificities of two tests are equal.
   Equivalence	Test if the sensitivities/specificities of two tests are equivalent within a practical difference.
   Non-inferiority	Test if the sensitivity/specificity of a new test is not inferior to a standard test.

   The default options use a Miettinen-Nurminen or Tango score confidence interval, and a Score Z test. The Newcombe score confidence interval is approximate not based on the same evidence function, and rejection of a hypothesis based on the confidence limits and hypothesis test may give conflicting results.

10. In the analysis task pane, under the hypotheses drop-down list:
    • If testing a hypothesis of equivalence, in the Equivalent difference, type the smallest practical difference that would be considered the same.
    • If testing a hypothesis of non-inferiority, in the Standard drop-down list, select the standard diagnostic test, and then in the Smallest difference edit box, type the smallest difference that would be considered inferior.
11. Optional: To compare the p-value against a predefined significance level, in the Significance level edit box, type the maximum probability of rejecting the null hypothesis when in fact it is true (typically 5% or 1%).
12. Click Calculate.