User Guide

419
Linear Regress
ion

Standardized. The residual divided by an estimate of its standard deviation.
Standardiz
ed residuals, which are also known as Pearson residuals, have a mean
of 0 and a standard deviation of 1.
 Studentized. The residual divided by an estimate of its standard deviation that
varies from case to case, depending on the distance of each case's values on the
independen
t variables from the means of the independent variables.
 Deleted. T
he residual for a case when that case is excluded from the calculation of
the regression coefficients. It is the difference between the value of the dependent
variable and the adjusted predicted value.
 Studentized dele ted. The deleted residual for a case divided by its standard
error. The
difference between a Studentized deleted residual and its associated
Studentized residual indicates how much difference eliminating a case makes
on its own prediction.
Influence Statistics. The change in the regression coefficients (DfBeta(s)) and
predicte
d values (DfFit) that results from the exclusion of a particular case.
Standardized DfBetas and DfFit values are also available along with the covariance
ratio.
 DfBeta(s). The difference in beta value is the change in the regression coefficient
that results from the exclusion of a particular case. A value is computed for each
term in th
e model, including the constant.
 Standar
dized DfBeta.
Standardized difference in beta value. The change in the
regression coefficient that results from the exclusion of a particular case. You
may want to examine cases with absolute values greater than 2 divided by the
square r
oot of N, where N is the number of cases. A value is computed for each
term in the model, including the constant.
 DfFit. The difference in fit value is the change in the predicted value that results
from the exclusion of a particular case.
 Standardized DfFit. Standardized difference in fit value. The change in the
predic
ted value that results from the exclusion of a particular case. You may want
to examine standardized values which in absolute value exceed 2 times the