Society of Actuaries (SOA) PA Practice Exam

What R package would you likely use to calculate the AUC in ROC analysis?

1. glmnet

2. pROC

3. caret

4. dplyr

The correct answer is: pROC

The pROC package is specifically designed for analyzing Receiver Operating Characteristic (ROC) curves and calculating the Area Under the Curve (AUC), which is a key metric for evaluating the performance of binary classification models. This package provides functions that allow for the easy computation of AUC values, along with visualizations of the ROC curves. It includes features to handle various data situations, such as adjusting for multiple groups or bootstrapping to assess the stability of the AUC estimate. The intuitive interface and specialized tools make pROC the go-to option for anyone needing to perform ROC analyses in R. In contrast, glmnet is primarily used for fitting generalized linear and similar models via penalized maximum likelihood, while caret is a comprehensive package that streamlines the process for building predictive models but is not focused on ROC analysis specifically. dplyr is designed for data manipulation and transformation, which does not pertain to ROC curve analysis or AUC computation directly.