On 11 Feb 2004 at 11:40, Rajarshi Guha wrote: Leverage is kind of Mahalanobis-distance in X-space, so make sense also for observations not used to estimate the model. (But maybe not the name!). High leverage for this points indicates that it is far from the points used to estimate the model, so you have really to trust the form of the model!
Kjetil Halvorsen > 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/ . > ================================================================= . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
