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The FACTOR Procedure

ODS Table Names

PROC FACTOR assigns a name to each table it creates. You can use these names to reference the table when using the Output Delivery System (ODS) to select tables and create output data sets. These names are listed in the following table. For more information on ODS, see Chapter 15, "Using the Output Delivery System."

Table 26.2: ODS Tables Produced in PROC FACTOR
ODS Table Name Description Option
AlphaCoefCoefficient alpha for each factorMETHOD=ALPHA
CanCorrSquared canonical correlationsMETHOD=ML
CondStdDevConditional standard deviationsSIMPLE w/PARTIAL
ConvergenceStatusConvergence statusMETHOD=PRINIT, =ALPHA, =ML, or =ULS
CorrCorrelationsCORR
EigenvaluesEigenvaluesdefault, SCREE
EigenvectorsEigenvectorsEIGENVECTORS
FactorWeightRotateFactor weights for rotationHKPOWER=
FactorPatternFactor patterndefault
FactorStructureFactor structureROTATE= any oblique rotation
FinalCommunFinal communalitiesdefault
FinalCommunWgtFinal communalities with weightsMETHOD=ML, METHOD=ALPHA
FitMeasuresMeasures of fitMETHOD=ML
ImageCoefImage coefficientsMETHOD=IMAGE
ImageCovImage covariance matrixMETHOD=IMAGE
ImageFactorsImage factor matrixMETHOD=IMAGE
InputFactorPatternInput factor patternPRINT
InputScoreCoefStandardized input scoring coefficientsMETHOD=SCORE
InterFactorCorrInter-factor correlationsROTATE= any oblique rotation
InvCorrInverse correlation matrixALL
IterHistoryIteration historyMETHOD=PRINIT, =ALPHA, =ML, or =ULS
MultipleCorrSquared multiple correlationsMETHOD=IMAGE or METHOD=HARRIS
NormObliqueTransNormalized oblique transformation matrixROTATE= any oblique rotation
ObliqueRotFactPatRotated factor patternROTATE= any oblique rotation
ObliqueTransOblique transformation matrixHKPOWER=
OrthRotFactPatRotated factor patternROTATE= any orthogonal rotation
OrthTransOrthogonal transformation matrixROTATE= any orthogonal rotation
ParCorrControlFactorPartial correlations controlling factorsRESIDUAL
ParCorrControlVarPartial correlations controlling other variablesMSA
PartialCorrPartial correlationsMSA, CORR w/PARTIAL
PriorCommunalEstPrior communality estimatesPRIORS=, METHOD=ML, METHOD=ALPHA
ProcrustesTargetTarget matrix for Procrustean transformationROTATE=PROCRUSTES, ROTATE=PROMAX
ProcrustesTransProcrustean transformation matrixROTATE=PROCRUSTES, ROTATE=PROMAX
RMSOffDiagPartialsRoot mean square off-diagonal partialsRESIDUAL
RMSOffDiagResidsRoot mean square off-diagonal residualsRESIDUAL
ReferenceAxisCorrReference axis correlationsROTATE= any oblique rotation
ReferenceStructureReference structureROTATE= any oblique rotation
ResCorrUniqueDiagResidual correlations with uniqueness on the diagonalRESIDUAL
SamplingAdequacyKaiser's measure of sampling adequacyMSA
SignifTestsSignificance testsMETHOD=ML
SimpleStatisticsSimple statisticsSIMPLE
StdScoreCoefStandardized scoring coefficientsSCORE
VarExplainVariance explaineddefault
VarExplainWgtVariance explained with weightsMETHOD=ML, METHOD=ALPHA
VarFactorCorrSquared multiple correlations of the variables with each factorSCORE
VarWeightRotateVariable weights for rotationNORM=WEIGHT, ROTATE=

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