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 Table 35.3. For more information about ODS, see Chapter 20: Using the Output Delivery System.
Table 35.3: ODS Tables Produced by 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 with 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 or 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 |
METHOD=PATTERN with PRINT or ALL |
InputScoreCoef |
Standardized input scoring coefficients |
METHOD=SCORE with PRINT or ALL |
InterFactorCorr |
Interfactor 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 |
NObs |
Number of records and observations, input data type |
default |
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 with PARTIAL |
PriorCommunalEst |
Prior communality estimates |
PRIORS=, METHOD=ML or ALPHA |
ProcrustesTarget |
Target matrix for Procrustean transformation |
ROTATE=PROCRUSTES, |
ProcrustesTrans |
Procrustean transformation matrix |
ROTATE=PROCRUSTES, |
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, or ALPHA |
VarFactorCorr |
Squared multiple correlations of the variables with each factor |
SCORE |
VarWeightRotate |
Variable weights for rotation |
NORM=WEIGHT, ROTATE= |