ROC曲线的数据怎么录入,想分析几种方法的诊断准确率

2025-03-16 06:58:26
推荐回答(1个)
回答1:

1、ROC的分析步骤:
①ROC曲线绘制。依据专业知识,对疾病组和参照组测定结果进行分析,确定测定值的上下限、组距以及截断点(cut-off point),按选择的组距间隔列出累积频数分布表,分别计算出所有截断点的敏感性、特异性和假阳性率(1-特异性)。以敏感性为纵坐标代表真阳性率,(1-特异性)为横坐标代表假阳性率,作图绘成ROC曲线。
②ROC曲线评价统计量计算。ROC曲线下的面积值在1.0和0.5之间。在AUC>0.5的情况下,AUC越接近于1,说明诊断效果越好。AUC在 0.5~0.7时有较低准确性,AUC在0.7~0.9时有一定准确性,AUC在0.9以上时有较高准确性。AUC=0.5时,说明诊断方法完全不起作用,无诊断价值。AUC<0.5不符合真实情况,在实际中极少出现。
③两种诊断方法的统计学比较。两种诊断方法的比较时,根据不同的试验设计可采用以下两种方法:①当两种诊断方法分别在不同受试者身上进行时,采用成组比较法。②如果两种诊断方法在同一受试者身上进行时,采用配对比较法。
2、受试者工作特征曲线 (receiver operating characteristic curve,简称ROC曲线),又称为感受性曲线(sensitivity curve)。得此名的原因在于曲线上各点反映着相同的感受性,它们都是对同一信号刺激的反应,只不过是在几种不同的判定标准下所得的结果而已。接受者操作特性曲线就是以虚报概率为横轴,击中概率为纵轴所组成的坐标图,和被试在特定刺激条件下由于采用不同的判断标准得出的不同结果画出的曲线。

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