中文摘要：

目的针对重复测量诊断数据,为同时考虑协变量对诊断试验准确性评价的影响,度量重复测量数据间的相关性,本文探索新的ROC曲线的建模方法。方法通过广义线性混合效应模型对ROC曲线进行模拟,并采用贝叶斯参数估计方法,利用Win BUGS软件予以实现,进而计算不同协变量取值下的ROC曲线下面积（AUC）以对诊断试验结果进行评价。结果实例数据分析结果表明,基于广义线性混合效应模型的ROC曲线建模方法可以有效地刻画重复测量诊断试验数据,给出更有解释意义的回归参数,提供临床分析的参考依据。结论基于广义线性混合效应的ROC曲线模型在解决重复测量诊断试验的准确度评价问题起着至关重要的作用。

英文摘要：

Objective To investigate the impact of covariates on diagnostic test and assess the correlation between repeated measurement data,this paper explores innovative modeling techniques of ROC curve. Methods We introduce the new ROC curve method based on generalized linear mixed effects model and apply Bayesian techniques to parameters estimationwith Winbugs Softw are. Further,areas under the ROC curve（ AUC）with different values of covariates could be calculated in terms of assessment. Results Cases analysis results indicate the proposed method efficiently explores the repeated measurement data and provides parameterswith practical significance,serving as a golden reference. Conclusion The ROC curve based on generalized linear mixed effects models can be effectively used to solve the test accuracy evaluation problem of the repeated diagnostic trials.