to compare the sensitivity, specificity and area under the ROC curve (AUC) of indices constructed using equal number of …, specificity and AUC of an index increase as the number of partitions of components increases. However, the rate that the … regression model for each component was proposed as potential weight. The current simulation results showed that the sensitivity …

addition, we give results that allow us to get all cut-off points that maximize a weighted combination of specificity and … sensitivity. In addition, we discuss measures of association between predicted probabilities and observed responses, and, in …

The accuracy of a binary diagnostic test is usually measured in terms of its sensitivity and its specificity, or …

rate, the false non-discovery rate, the sensitivity and the specificity. The results can provide guidance on how to select …

sensitivity and specificity are the most popular measures of accuracy for diagnostic tests. Available methods for analyzing … address missing data and other related issues for modeling sensitivity and specificity within such a time-varying reference …

Influence functions are commonly used as diagnostic tools in order to investigate sensitivity aspects in principal … component analysis. This paper suggests a practical alternative for the eigenvalues by introducing a sensitivity measure derived …

. However, the resulting receiver operating characteristic (ROC) curve is only defined in a subrange (L, h) of false … markers, especially when ROC curves from multiple tests cross. The resulting ROC is defined in the whole range of (0,1) and is …