A binary diagnostic test is a medical test that is applied to an individual in order to determine the presence or the absence of a certain disease and whose result can be positive or negative. A positive result indicates the presence of the disease, and a negative result indicates the absence. Positive and negative predictive values represent the accuracy of a binary diagnostic test when it is applied to a cohort of individuals, and they are measures of the clinical accuracy of the binary diagnostic test. In this manuscript, we study the comparison of the positive (negative) predictive values of two binary diagnostic tests subject to a paired design through confidence intervals. We have studied confidence intervals for the difference and for the ratio of the two positive (negative) predictive values. Simulation experiments have been carried out to study the asymptotic behavior of the confidence intervals, giving some general rules for application. We also study a method to calculate the sample size to compare the parameters using confidence intervals. We have written a program in R to solve the problems studied in this manuscript. The results have been applied to the diagnosis of colorectal cancer.

中文翻译：

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比较两个诊断测试的预测值的置信区间和样本量

二元诊断测试是一种医学测试，适用于个人以确定某种疾病的存在或不存在，其结果可以是阳性或阴性。阳性结果表明存在疾病，阴性结果表明不存在。阳性和阴性预测值代表二元诊断测试应用于一组个体时的准确性，它们是二元诊断测试临床准确性的度量。在这份手稿中，我们通过置信区间研究了受配对设计影响的两个二元诊断测试的阳性（阴性）预测值的比较。我们研究了两个正（负）预测值的差异和比率的置信区间。已经进行了模拟实验来研究置信区间的渐近行为，给出了一些应用的一般规则。我们还研究了一种计算样本量的方法，以使用置信区间来比较参数。我们已经用 R 编写了一个程序来解决本手稿中研究的问题。研究结果已应用于结直肠癌的诊断。