Table 3.

Quantities sensitive to choices of variable category cut point values

Number and proportion of units within the category

Measures of association (relative and absolute)*

Model fit statistics (e.g. AIC, BIC)

P-values

Hypothesis test statistics

Correlations*

Splines

Sensitivity*

Specificity*

Positive Predictive Value*

Negative Predictive Value*

C-statistic, i.e. area under ROC curve*

C-index

Predicted probability of an outcome

Event Net Reclassification Index*

Non-Event Net Reclassification Index*

Integrated Discrimination Improvement*

Reclassification Calibration Statistic*

Number and proportion of units reclassified across outcome risk categories

The list in this table is not exhaustive.

^*Both magnitude and precision of the measure sensitive to cut point selection.

AIC=Akaike Information Criterion, BIC=Bayesian Information Criterion, ROC=Receiver Operating Characteristic