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Using Bayes theorem to estimate positive and negative predictive values for continuously and ordinally scaled diagnostic tests
International Journal of Methods in Psychiatric Research ( IF 3.1 ) Pub Date : 2021-03-02 , DOI: 10.1002/mpr.1868
Felix Fischer 1
Affiliation  

Positive predictive values (PPVs) and negative predictive values (NPVs) are frequently reported to put estimates of accuracy of a diagnostic test in clinical context and to obtain risk estimates for a given patient taking into account baseline prevalence in the population. In order to calculate PPV and NPV, tests with ordinally or continuously scaled results are commonly dichotomized at the expense of a loss of information.

中文翻译:

使用贝叶斯定理估计连续和有序规模诊断测试的阳性和阴性预测值

经常报告阳性预测值 (PPV) 和阴性预测值 (NPV) 以将诊断测试的准确性估计值置于临床环境中,并在考虑到人群中的基线患病率的情况下获得给定患者的风险估计值。为了计算 PPV 和 NPV,通常会以丢失信息为代价将具有有序或连续缩放结果的测试分成两部分。
更新日期:2021-03-02
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