Output Data Sets
The OUT= Data Set
The OUT= data set contains all the data in the DATA=
data set plus new variables called Factor1, Factor2,
and so on, containing estimated factor scores.
If more than 99 factors are requested, the new
variable names are Fact1, Fact2, and so on.
Each estimated factor score is computed as a linear combination
of the standardized values of the variables that are factored.
The coefficients are always displayed if the OUT= option is
specified and are labeled "Standardized Scoring Coefficients."
The OUTSTAT= Data Set
The OUTSTAT= data set is similar to the TYPE=CORR or TYPE=UCORR
data set produced by the CORR procedure, but it is a TYPE=FACTOR data
set and it
contains many results in addition to those produced by PROC CORR.
The OUTSTAT= data set contains observations with
_TYPE_='UCORR' and _TYPE_='USTD'
if you specify the NOINT option.
The output data set contains the following variables:
- the BY variables, if any
- two new character variables, _TYPE_ and _NAME_
- the variables analyzed, that is, those in the VAR
statement, or, if there is no VAR statement, all
numeric variables not listed in any other statement.
Each observation in the output data set contains some
type of statistic as indicated by the _TYPE_ variable.
The _NAME_ variable is blank except where otherwise indicated.
The values of the _TYPE_ variable are as follows:
- _TYPE_
- Contents
- MEAN
- means
- STD
- standard deviations
- USTD
- uncorrected standard deviations
- N
- sample size
- CORR
- correlations.
The _NAME_ variable contains the name of the variable
corresponding to each row of the correlation matrix.
- UCORR
- uncorrected correlations.
The _NAME_ variable contains the name of the variable
corresponding to each row of the uncorrected correlation matrix.
- IMAGE
- image coefficients.
The _NAME_ variable contains the name of the variable
corresponding to each row of the image coefficient matrix.
- IMAGECOV
- image covariance matrix.
The _NAME_ variable contains the name of the variable
corresponding to each row of the image covariance matrix.
- COMMUNAL
- final communality estimates
- PRIORS
- prior communality estimates, or estimates
from the last iteration for iterative methods
- WEIGHT
- variable weights
- SUMWGT
- sum of the variable weights
- EIGENVAL
- eigenvalues
- UNROTATE
- unrotated factor pattern.
The _NAME_ variable contains the name of the factor.
- RESIDUAL
- residual correlations.
The _NAME_ variable contains the name of the variable
corresponding to each row of the residual correlation matrix.
- PRETRANS
- transformation matrix from prerotation.
The _NAME_ variable contains the name of the factor.
- PREROTAT
- factor pattern from prerotation.
The _NAME_ variable contains the name of the factor.
- TRANSFOR
- transformation matrix from rotation.
The _NAME_ variable contains the name of the factor.
- FCORR
- interfactor correlations.
The _NAME_ variable contains the name of the factor.
- PATTERN
- factor pattern.
The _NAME_ variable contains the name of the factor.
- RCORR
- reference axis correlations.
The _NAME_ variable contains the name of the factor.
- REFERENC
- reference structure.
The _NAME_ variable contains the name of the factor.
- STRUCTUR
- factor structure.
The _NAME_ variable contains the name of the factor.
- SCORE
- scoring coefficients.
The _NAME_ variable contains the name of the factor.
- USCORE
- scoring coefficients to be applied without
subtracting the mean from the raw variables.
The _NAME_ variable contains the name of the factor.
Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.
