连续比例逻辑斯蒂回归模型在半参数ROC曲面估计上的应用

Application of Continuation Ratio Logistic Regression Model to Semi-parametric ROC Surface Estimation

针对诊断试验中有3种或3种以上诊断结果的情形,常采用ROC曲面来代替ROC曲线进行试验准确度的判断。回顾以往有关ROC曲面估计问题的文献,可以发现学者们大多使用的是参数方法和非参数方法,而利用半参数方法所得到的结果也很优良,结合连续比例逻辑斯蒂回归模型和bootstrap方法,所得到的ROC曲面和非参数方法相比更加平滑,也更加精确,在计算半参数最大似然估计时,半参数方法可以借助许多统计软件中的逻辑斯蒂程序来代替传统的牛顿迭代法之类的数值计算方法,能很快得到结果。因此在ROC曲面估计问题上半参数方法明显优于非参数方法。

For the situation of three or more diagnostic results in a diagnostic test,we often use ROC surface instead of ROC curve to judge the accuracy of the test.Reviewing the previous literature on ROC surface estimation,we can find that many scholars use parametric methods and non-parametric methods,and the results obtained by using semi-parametric methods are also excellent.Combining continuation ratio logistic regression model and bootstrap method,it can be found that the ROC surface obtained is smoother and more accurate than that of the non-parametric method.When calculating the semi-parametric maximum likelihood estimation,the semi-parametric method can use some logistic programs in some statistical software to replace the Newton’s method,which can quickly get results.Therefore,the semi-parametric method is obviously better than the non-parametric method in the ROC surface estimation problem.