PROC TRANSREG Statement

The TRANSREG Procedure

PROC TRANSREG Statement

PROC TRANSREG < DATA=SAS-data-set >
< OUTTEST=SAS-data-set > < a-options > < o-options > ;

The PROC TRANSREG statement starts 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= and OUTTEST= options can appear only in the PROC TRANSREG statement.

The following table summarizes options available in the PROC TRANSREG statement. All a-options and o-options are described in the sections on either the MODEL or OUTPUT statement, in which these options can also be specified.

Table 65.1: Options Available in the TRANSREG Procedure

Task	Option	Statement
Identify input data set
specifies input SAS data set	DATA=	PROC
Output data set with test statistics
specifies output test statistics data set	OUTTEST=	PROC
Input data set
specifies input observation type	TYPE=	MODEL
restarts iterations	REITERATE	MODEL
Specify method and control iterations
specifies minimum criterion change	CCONVERGE=	MODEL
specifies minimum data change	CONVERGE=	MODEL
specifies canonical dummy-variable initialization	DUMMY	MODEL
specifies maximum number of iterations	MAXITER=	MODEL
specifies iterative algorithm	METHOD=	MODEL
specifies number of canonical variables	NCAN=	MODEL
specifies singularity criterion	SINGULAR=	MODEL
Control missing data handling
includes monotone special missing values	MONOTONE=	MODEL
excludes observations with missing values	NOMISS	MODEL
unties special missing values	UNTIE=	MODEL
Control intercept and CLASS variables
CLASS dummy variable name prefix	CPREFIX=	MODEL
CLASS dummy variable label prefix	LPREFIX=	MODEL
no intercept or centering	NOINT	MODEL
order of class variable levels	ORDER=	MODEL
controls output of reference levels	REFERENCE=	MODEL
CLASS dummy variable label separators	SEPARATORS=	MODEL
Control displayed output
confidence limits alpha	ALPHA=	MODEL
displays parameter estimate confidence limits	CL	MODEL
displays model specification details	DETAIL	MODEL
displays iteration histories	HISTORY	MODEL
suppresses displayed output	NOPRINT	MODEL
suppresses the iteration histories	SHORT	MODEL
displays regression results	SS2	MODEL
displays ANOVA table	TEST	MODEL
displays conjoint part-worth utilities	UTILITIES	MODEL
Control standardization
fits additive model	ADDITIVE	MODEL
do not zero constant variables	NOZEROCONSTANT	MODEL
specifies transformation standardization	TSTANDARD=	MODEL
Predicted values, residuals, scores
outputs canonical scores	CANONICAL	OUTPUT
outputs individual confidence limits	CLI	OUTPUT
outputs mean confidence limits	CLM	OUTPUT
specifies design matrix coding	DESIGN=	OUTPUT
outputs leverage	LEVERAGE	OUTPUT
does not restore missing values	NORESTOREMISSING	OUTPUT
suppresses output of scores	NOSCORES	OUTPUT
outputs predicted values	PREDICTED	OUTPUT
outputs redundancy variables	REDUNDANCY=	OUTPUT
outputs residuals	RESIDUALS	OUTPUT
Output data set replacement
replaces dependent variables	DREPLACE	OUTPUT
replaces independent variables	IREPLACE	OUTPUT
replaces all variables	REPLACE	OUTPUT
Output data set coefficients
outputs coefficients	COEFFICIENTS	OUTPUT
outputs ideal point coordinates	COORDINATES	OUTPUT
outputs marginal means	MEANS	OUTPUT
outputs redundancy analysis coefficients	MREDUNDANCY	OUTPUT
Output data set variable name prefixes
dependent variable approximations	ADPREFIX=	OUTPUT
independent variable approximations	AIPREFIX=	OUTPUT
canonical dependent variables	CDPREFIX=	OUTPUT
conservative individual lower CL	CILPREFIX=	OUTPUT
canonical independent variables	CIPREFIX=	OUTPUT
conservative-individual-upper CL	CIUPREFIX=	OUTPUT
conservative-mean-lower CL	CMLPREFIX=	OUTPUT
conservative-mean-upper CL	CMUPREFIX=	OUTPUT
METHOD=MORALS untransformed dependent	DEPENDENT=	OUTPUT
liberal-individual-lower CL	LILPREFIX=	OUTPUT
liberal-individual-upper CL	LIUPREFIX=	OUTPUT
liberal-mean-lower CL	LMLPREFIX=	OUTPUT
liberal-mean-upper CL	LMUPREFIX=	OUTPUT
residuals	RDPREFIX=	OUTPUT
predicted values	PPREFIX=	OUTPUT
redundancy variables	RPREFIX=	OUTPUT
transformed dependents	TDPREFIX=	OUTPUT
transformed independents	TIPREFIX=	OUTPUT
Output data set macros
creates macro variables	MACRO	OUTPUT
Output data set details
dependent and independent approximations	APPROXIMATIONS	OUTPUT
canonical correlation coefficients	CCC	OUTPUT
canonical elliptical point coordinate	CEC	OUTPUT
canonical point coordinates	CPC	OUTPUT
canonical quadratic point coordinates	CQC	OUTPUT
approximations to transformed dependents	DAPPROXIMATIONS	OUTPUT
approximations to transformed independents	IAPPROXIMATIONS	OUTPUT
elliptical point coordinates	MEC	OUTPUT
point coordinates	MPC	OUTPUT
quadratic point coordinates	MQC	OUTPUT
multiple regression coefficients	MRC	OUTPUT

DATA=SAS-data-set: specifies the SAS data set to be analyzed. If you do not specify the DATA= option, PROC TRANSREG uses the most recently created SAS data set. The data set must be an ordinary SAS data set; it cannot be a special TYPE= data set.
OUTTEST=SAS-data-set: specifies an output data set to contain hypothesis tests results. When you specify the OUTTEST= option, the data set contains ANOVA results. When you specify the SS2 a-option, regression tables are also output. When you specify the UTILITIES o-option, conjoint analysis part-worth utilities are also output.

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