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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 AlphaCoef Coefficient alpha for each factor METHOD=ALPHA CanCorr Squared canonical correlations METHOD=ML CondStdDev Conditional standard deviations SIMPLE w/PARTIAL ConvergenceStatus Convergence status METHOD=PRINIT, =ALPHA, =ML, or =ULS Corr Correlations CORR Eigenvalues Eigenvalues default, SCREE Eigenvectors Eigenvectors EIGENVECTORS FactorWeightRotate Factor weights for rotation HKPOWER= FactorPattern Factor pattern default FactorStructure Factor structure ROTATE= any oblique rotation FinalCommun Final communalities default FinalCommunWgt Final communalities with weights METHOD=ML, METHOD=ALPHA FitMeasures Measures of fit METHOD=ML ImageCoef Image coefficients METHOD=IMAGE ImageCov Image covariance matrix METHOD=IMAGE ImageFactors Image factor matrix METHOD=IMAGE InputFactorPattern Input factor pattern PRINT InputScoreCoef Standardized input scoring coefficients METHOD=SCORE InterFactorCorr Inter-factor correlations ROTATE= any oblique rotation InvCorr Inverse correlation matrix ALL IterHistory Iteration history METHOD=PRINIT, =ALPHA, =ML, or =ULS MultipleCorr Squared multiple correlations METHOD=IMAGE or METHOD=HARRIS NormObliqueTrans Normalized oblique transformation matrix ROTATE= any oblique rotation ObliqueRotFactPat Rotated factor pattern ROTATE= any oblique rotation ObliqueTrans Oblique transformation matrix HKPOWER= OrthRotFactPat Rotated factor pattern ROTATE= any orthogonal rotation OrthTrans Orthogonal transformation matrix ROTATE= any orthogonal rotation ParCorrControlFactor Partial correlations controlling factors RESIDUAL ParCorrControlVar Partial correlations controlling other variables MSA PartialCorr Partial correlations MSA, CORR w/PARTIAL PriorCommunalEst Prior communality estimates PRIORS=, METHOD=ML, METHOD=ALPHA ProcrustesTarget Target matrix for Procrustean transformation ROTATE=PROCRUSTES, ROTATE=PROMAX ProcrustesTrans Procrustean transformation matrix ROTATE=PROCRUSTES, ROTATE=PROMAX RMSOffDiagPartials Root mean square off-diagonal partials RESIDUAL RMSOffDiagResids Root mean square off-diagonal residuals RESIDUAL ReferenceAxisCorr Reference axis correlations ROTATE= any oblique rotation ReferenceStructure Reference structure ROTATE= any oblique rotation ResCorrUniqueDiag Residual correlations with uniqueness on the diagonal RESIDUAL SamplingAdequacy Kaiser's measure of sampling adequacy MSA SignifTests Significance tests METHOD=ML SimpleStatistics Simple statistics SIMPLE StdScoreCoef Standardized scoring coefficients SCORE VarExplain Variance explained default VarExplainWgt Variance explained with weights METHOD=ML, METHOD=ALPHA VarFactorCorr Squared multiple correlations of the variables with each factor SCORE VarWeightRotate Variable weights for rotation NORM=WEIGHT, ROTATE=

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