In a statistical model, what does the threshold value represent in relation to the sensitivity of predictors?

In a statistical model the threshold value is the cut‑off you choose to decide whether a predictor’s output signals a positive outcome or not; it is the point at which you say “yes” or “no. ” Sensitivity, or true‑positive rate, measures how often the model correctly flags positives when the threshold is low, so lowering the threshold usually increases sensitivity but may also raise false positives. Conversely, raising the threshold reduces sensitivity because fewer cases are counted as positive. For example, in a medical test, if the threshold for a blood marker is set very low, the test will flag many patients as sick (high sensitivity) but may also incorrectly label healthy people as sick. Thus the threshold directly controls how sensitive the model is to detecting true positives.