Rembold C M, Watson D
Department of Internal Medicine, University of Virginia Medical Center, Charlottesville.
Ann Intern Med. 1988 Jan;108(1):115-20. doi: 10.7326/0003-4819-108-1-115.
This article reintroduces a different form of Bayes' theorem that allows calculation of posttest probabilities by adding quantities known as "weights." A weight combines information found in both a test's sensitivity and specificity. A single value can describe how a given test result changes the posttest probability of disease. The use of weights and this form of Bayes' theorem should allow more widespread understanding and use of probability theory in clinical practice.
本文重新引入了贝叶斯定理的一种不同形式，该形式允许通过添加被称为“权重”的量来计算检验后概率。权重结合了在检验的灵敏度和特异度中发现的信息。单个值可以描述给定的检验结果如何改变疾病的检验后概率。权重的使用以及这种形式的贝叶斯定理应能使概率理论在临床实践中得到更广泛的理解和应用。
