  Positive predictive value and negative predictive value are two widely used
parameters to assess the clinical usefulness of a medical diagnostic test. When
there are two diagnostic tests, it is recommendable to make a comparative
assessment of the values of these two parameters after applying the two tests
to the same subjects (paired samples). The objective is then to make individual
or global inferences about the difference or the ratio of the predictive value
of the two diagnostic tests. These inferences are usually based on complex and
not very intuitive expressions, some of which have subsequently been
reformulated. We define the two properties of symmetry which any inference
method must verify - symmetry in diagnoses and symmetry in the tests -, we
propose new inference methods, and we define them with simple expressions. All
of the methods are compared with each other, selecting the optimal method: (a)
to obtain a confidence interval for the difference or ratio; (b) to perform an
individual homogeneity test of the two predictive values; and (c) to carry out
a global homogeneity test of the two predictive values.
