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 Table 34.3. For more information about ODS, see Chapter 20, Using the Output Delivery System.

Table 34.3 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
METHOD=HARRIS

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,
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, or ALPHA

VarFactorCorr

Squared multiple correlations of the variables with each factor

SCORE

VarWeightRotate

Variable weights for rotation

NORM=WEIGHT, ROTATE=