Table 3.

Examples for comparison of errors and their interpretation.

Comparison	Usefulness/Interpretation
True positives vs. False negatives	This comparison informs whether patients incorrectly excluded from the study cohort differ from those correctly included with respect to patient characteristics or outcomes. If true positive and false negative patients appear similar: Model misclassification may be random and excluded patients will most likely have a minimal impact on analysis results. If true positive and false negative patients appear different: Model misclassification may be systematic and excluded patients may impact analysis results.
True positives vs. False positives	This comparison informs whether patients incorrectly included in the study cohort differ from those correctly included with respect to patient characteristics or outcomes. If true positive and false positive patients appear similar: Model misclassification may be random and incorrectly included patients may have a minimal impact on analysis results. If true positive and false positive patients appear different: Model misclassification may be systematic and incorrectly including patients may impact analysis results.