I've created ROC curves by calculating the TPR and FPR at various thresholds. The FPR range differs between models, so I'm wondering if AUC is still a valid way to compare the curves. A curve will have a low AUC value if it has a small FPR range, but this doesn't make it a worse model, does it?
Sidenote: These aren't machine learning models. I'm considering subsets of biological data as a model, and comparing results from each subset to those of the complete dataset to determine the accuracy of results.