Comparison of predictive values with paired samples

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. We define the two properties of symmetry which any inference method must verify, we propose new inference methods, and we define them with simple expressions. All of the methods are compared with each other, concluding that the optimal method is: (1) in the case of a confidence interval for the difference or ratio, respectively, the classic method of Wang et al. and the new method that is proposed, both methods applied to the original data increased by 0.5; (2) in the case of individual homogeneity test of the two predictive values, the new method with the predictive values estimated subject to the null hypothesis; (3) in the case of a global homogeneity test of the two predictive values, the new method.