What is the Trade-off Between Sensitivity and Specificity?
Improving one often comes at the expense of the other. For instance, increasing sensitivity may lead to more false positives, reducing specificity. Conversely, increasing specificity may result in more false negatives, reducing sensitivity. This trade-off is known as the ROC curve, which helps in selecting the optimal cut-off point for the test.
