Modeling and Multivariate Methods - SAS

Chapter 3 Fitting Standard Least Squares Models 105
Save Columns
Table 3.10 Description of the Save Columns Options (Continued)
Residuals
Mean Confidence
Interval
Indiv Confidence
Interval
Studentized Residuals
Hats
Std Error of Predicted
Std Error of Residual
Std Error of Individual
Effect Leverage Pairs
Creates a new column called Residual colname that contains the residuals,
which are the observed response values minus predicted values.
Creates two new columns called Lower 95% Mean colname and Upper
95% Mean colname. The new columns contain the lower and upper 95%
confidence limits for the line of fit.
Note: If you hold down the SHIFT key and select the option, you are
prompted to enter an α-level for the computations.
Creates two new columns called Lower 95% Indiv colname and
Upper 95% Indiv colname. The new columns contain lower and upper
95% confidence limits for individual response values.
Note: If you hold down the SHIFT key and select the option, you are
prompted to enter an α-level for the computations.
Creates a new column called Studentized Resid colname. The new column
values are the residuals divided by their standard error.
Creates a new column called h colname. The new column values are the
diagonal values of the matrix XX'X ( ) – 1 X' , sometimes called hat values.
Creates a new column called StdErr Pred colname that contains the
standard errors of the predicted values.
Creates a new column called StdErr Resid colname that contains the
standard errors of the residual values.
Creates a new column called StdErr Indiv colname that contains the
standard errors of the individual predicted values.
Creates a set of new columns that contain the values for each leverage plot.
The new columns consist of an X and Y column for each effect in the model.
The columns are named as follows. If the response column name is R and
the effects are X1 and X2, then the new column names are:
X Leverage of X1 for R
X Leverage of X2 for R
Y Leverage of X1 for R
Y Leverage of X2 for R
Cook’s D Influence
StdErr Pred Formula
Saves the Cook’s D influence statistic. Influential observations are those that,
according to various criteria, appear to have a large influence on the
parameter estimates.
Creates a new column called PredSE colname that contains the standard
error of the predicted values. It is the same as the Std Error of Predicted
option, but it saves the formula with the column. Also, it can produce very
large formulas.