The PROC TRANSREG statement invokes the TRANSREG procedure. Optionally, this statement identifies an input and an OUTTEST= data set, specifies the algorithm and other computational details, requests displayed output, and controls the contents of the OUT= data set (which is created with the OUTPUT statement). The DATA=, OUTTEST=, and PLOTS= options can appear only in the PROC TRANSREG statement. Table 104.1 summarizes the options available in the PROC TRANSREG statement. The aoptions are also available in the MODEL statement, and the ooptions are also available in the OUTPUT statement.
Table 104.1: Options Available in the PROC TRANSREG Statement
Option 
Description 

Data Set Options (PROC Statement) 

Specifies input SAS data set 

Specifies output test statistics data set 

ODS Graphics (PROC Statement) 

Specifies ODS Graphics selection 

Input Control (PROC or MODEL) 

Restarts the iterations 

Specifies input observation type 

Method and Iterations (PROC or MODEL) 

Specifies minimum criterion change 

Specifies minimum data change 

Specifies maximum number of iterations 

Specifies iterative algorithm 

Specifies number of canonical variables 

Specifies no restrictions on smoothing models 

Specifies singularity criterion 

Attempts direct solution instead of iteration 

Missing Data Handling (PROC or MODEL) 

Fits each model individually (METHOD=MORALS) 

Includes monotone special missing values 

Excludes observations with missing values 

Unties special missing values 

Intercept and CLASS Variables (PROC or MODEL) 

Specifies CLASS coded variable name prefix 

Specifies CLASS coded variable label prefix 

Specifies no intercept or centering 

Specifies order of CLASS variable levels 

Controls output of reference levels 

Controls CLASS coded variable label separators 

Control Displayed Output (PROC or MODEL) 

Specifies confidence limits alpha 

Displays parameter estimate confidence limits 

Displays model specification details 

Displays iteration histories 

Suppresses displayed output 

Prints the BoxCox log likelihood table 

Displays the R square 

Suppresses the iteration histories 

Displays regression results 

Displays ANOVA table 

Shortens transformed variable labels 

Displays conjoint partworth utilities 

Standardization (PROC or MODEL) 

Fits additive model 

Does not zero constant variables 

Specifies transformation standardization 

Predicted Values, Residuals, Scores (PROC or OUTPUT) 

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 (PROC or OUTPUT) 

Outputs coefficients 

Outputs ideal point coordinates 

Outputs marginal means 

Outputs redundancy analysis coefficients 

Output Data Set Variable Name Prefixes (PROC or OUTPUT) 

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 predicted values 

Specifies residuals 

Specifies redundancy variables 

Specifies transformed dependents 

Specifies transformed independents 

Macros Variables (PROC or OUTPUT) 

Creates macro variables 

Other Options (PROC or OUTPUT) 

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 