A receiver operating characteristic (ROC) curve is a graph that shows the diagnostic capability of a continuous variable at various thresholds predicting a binary outcome. This graph shows the relationship between the true positive rate to the false positive rate at different threshold values of the predictor variable. Different algorithms for defining the optimal threshold value will be discussed as well as assessing the predictive power of the variable.
In this workshop, we will
- review the binary logistic regression model
- Learn how to interpret an ROC curve
- Cover various diagnostic measures, such as: sensitivity, specificity, and area under the curve
- Discuss optimal thresholds of an ROC curve