Regressions with Discrete Dependent Variables: The Effect on R ²

0.5 to 7.5. Whenever it falls in the range 0.5 to 1.5, the subject checks Level 1; from 1.5 to 2.5, he checks Level 2, and so on. This procedure gives a perfect scaling technique. The assumption of a perfect model is merely that when the true attribute has a value x (anywhere in the continuum from 0.5 to 7.5), the model predicts this same value. The question is now very simple, since correlation between the true attribute value and the predicted value has been defined as 1.0. However, what