The OUTPUT statement creates a new SAS data set that contains coefficients, marginal means, and information about the original
and transformed variables. The information about original and transformed variables composes the score partition of the data
set; observations have _TYPE_
=’SCORE’. The coefficients and marginal means compose the coefficient partition of the data set; observations have _TYPE_
=’M COEFFI’ or _TYPE_
=’MEAN’. Other values of _TYPE_ are possible; for details, see "_TYPE_
and _NAME_
Variables" later in this chapter. For details about data set structure, see the section Output Data Set. To specify the name of the output data set, use the OUT=
option.
To control the contents of the data set and variable names, use one or more of the ooptions. You can also specify these options in the PROC TRANSREG statement.
Table 104.5 summarizes the options available in the OUTPUT statement. These options include the OUT= option and all of the ooptions. Many of the statistics created in the OUTPUT statement are exactly the same as statistics created by PROC REG. More details are given in the sections Predicted and Residual Values, Model Fit and Diagnostic Statistics in Chapter 85: The REG Procedure, and Chapter 4: Introduction to Regression Procedures.
Table 104.5: Options Available in the OUTPUT Statement
Option 
Description 

Identify output data set 

Outputs data set 

Predicted Values, Residuals, Scores 

Outputs canonical scores 

Outputs individual confidence limits 

Outputs mean confidence limits 

Specifies design matrix coding 

Replaces dependent variables 

Replaces independent variables 

Outputs leverage 

Does not restore missing values 

Suppresses output of scores 

Outputs predicted values 

Outputs redundancy variables 

Replaces all variables 

Outputs residuals 

Output Data Set Coefficients 

Outputs coefficients 

Outputs ideal point coordinates 

Outputs marginal means 

Outputs redundancy analysis coefficients 

Output Data Set Variable Name Prefixes 

Specifies dependent variable approximations 

Specifies independent variable approximations 

Specifies canonical dependent variables 

Specifies conservative individual lower CL 

Specifies canonical independent variables 

Specifies conservativeindividualupper CL 

Specifies conservativemeanlower CL 

Specifies conservativemeanupper CL 

Specifies METHOD=MORALS untransformed dependent 

Specifies liberalindividuallower CL 

Specifies liberalindividualupper CL 

Specifies liberalmeanlower CL 

Specifies liberalmeanupper CL 

Specifies residuals 

Specifies predicted values 

Specifies redundancy variables 

Specifies transformed dependents 

Specifies transformed independents 

Macros Variables 

Creates macro variables 

Other Options 

Outputs dependent and independent approximations 

Outputs canonical correlation coefficients 

Outputs canonical elliptical point coordinates 

Outputs canonical point coordinates 

Outputs canonical quadratic point coordinates 

Outputs approximations to transformed dependents 

Outputs approximations to transformed independents 

Outputs elliptical point coordinates 

Outputs point coordinates 

Outputs quadratic point coordinates 

Outputs multiple regression coefficients 
For the coefficients partition, the COEFFICIENTS , COORDINATES , and MEANS ooptions provide the coefficients that are appropriate for your model. For more explicit control of the coefficient partition, use the options that control details and prefixes. The following list provides details about these options.