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.

翻译：阳性预测值与阴性预测值是评估医学诊断试验临床实用性的两个常用参数。当存在两种诊断试验时，建议将两种试验应用于相同受试者（配对样本）后，对这两个参数的值进行比较评估。其目的在于对两种诊断试验预测值的差异或比值进行个体或整体推断。此类推断通常基于复杂且不够直观的表达式，其中部分表达式后来已被重新表述。我们定义了任何推断方法都必须满足的两个对称性——诊断对称性与试验对称性，提出了新的推断方法，并用简洁的表达式予以定义。所有方法均经过相互比较，从而筛选出最优方法用于：（a）获取差异或比值的置信区间；（b）执行两种预测值的个体同质性检验；（c）实施两种预测值的整体同质性检验。