Hi, I know that when I create a multiple linear regression model I can evaluate leverage values for the points used to create the model.
>From what I understand leverage gives an indication of how much a given observation affects the coefficients in the model. Thus when I use the model to predict values for some unknown observations (ie observations not used to create the model) calculating leverage values for these observations does not make sense - is this correct? If the above is true is there any measure that I could use (apart from R2 values or residuals) that I can use to obtain some indication of how the good the coefficients are when predicting unknown observations (sort of a 'reverse leverage' value)? Thanks, . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
