中文摘要：

目的 旨在提出一种Monte Carlo模拟方法,对具有相关关系的灵敏度和特异度进行计算机模拟,并运用其相关系数估计值的均方根误及偏差对该模拟方法的有效性进行评价;进而探讨分析具有相关关系的灵敏度和特异度数据时单样本Youden指数u检验方法的可靠性。方法 将诊断试验的四格表资料看成来自服从四元正态分布总体的样本,借助R语言的mvrnorm函数产生四格表资料,其满足灵敏度和特异度之间的总体相关系数。计算相关系数估计值的均方根误及偏差,并计算Youden指数u检验的第I类错误率与检验效能。结果 相关系数估计值的均方根误及偏差均较小。当相关系数ρ为0时,u检验能很好地控制犯第I类错误的概率;然而,当ρ不是0时,u检验的结果偏保守,并且随着｜ρ｜的增加,其结果偏离0.05更甚。结论 本文提出的具有相关关系灵敏度和特异度的M onte Carlo模拟方法能真实地反应灵敏度和特异度之间的相关性;当相关性强时,Youden指数u检验的前提假设不正确。

英文摘要：

Objective This study aims to propose a Monte Carlo simulation method to generate the correlated sensitivity and specificity in diagnostic trials, and then calculate the root mean squared error （RMSE） and bias of the estimate of the correlation coefficient between them so as to assess the validity of the proposed simulation method. Further, we study the reliability of the existing u test for single sample Youden index based on the data where the sensitivity and specificity are correlated. Methods In the simulation study, the diagnostic test data are considered to be generated from a four-dimensional normal distribution and the four-fold table data in the diagnostic test are generated from the mvrnorm function in R, where the sample correlation coefficient between the sensitivity and specificity is kept close to the population correlation coefficient ρ. As such, the corresponding RMSE and bias, the type I error rate and power can be calculated. Results Both the RMSE and bias are very small. When ρ is 0, the u test can control the type I error rate well. However, when ρ is not 0, the u test is conservative. Further, with the increase of ｜ ρ ｜, the type I error rate is much more faraway from 0. 05. Conclusion The Monte Carlo simulation method proposed in this article can effectively simulate the correlation relationship between the sensitivity and specificity. When there is a strong correlation between the sensitivity and specificity, the independence assumption between them is not so reasonable for the u test of single sample Youden index in diagnostic test.