Chapter Contents
Chapter Contents
Previous
Previous
Next
Next
The VARCLUS Procedure

Output Data Sets

OUTSTAT= Data Set

The OUTSTAT= data set is TYPE=CORR, and it can be used as input to the SCORE procedure or a subsequent run of PROC VARCLUS. The variables it contains are

The values of the _TYPE_ variable are listed in the following table.

Table 68.2: _TYPE_ Value and Statistic
_TYPE_ Contents
MEANmeans
STDstandard deviations
USTDuncorrected standard deviations, produced when the NOINT option is specified
Nnumber of observations
CORRcorrelations
UCORRuncorrected correlation matrix, produced when the NOINT option is specified
MEMBERSnumber of members in each cluster
VAREXPvariance explained by each cluster
PROPORproportion of variance explained by each cluster
GROUPnumber of the cluster to which each variable belongs
RSQUAREDsquared multiple correlation of each variable with its cluster component
SCOREstandardized scoring coefficients
USCOREscoring coefficients to be applied without subtracting the mean from the raw variables, produced when the NOINT option is specified
STRUCTURcluster structure
CCORRcorrelations between cluster components

The observations with _TYPE_='MEAN', 'STD', 'N', and 'CORR' have missing values for the _NCL_ variable. All other values of the _TYPE_ variable are repeated for each cluster solution, with different solutions distinguished by the value of the _NCL_ variable. If you want to specify the OUTSTAT= data set with the SCORE procedure, you can use a DATA step to select observations with the _NCL_ variable missing or equal to the desired number of clusters. Alternatively, you can use a WHERE clause, as follows.

   proc score score=s (where=(_ncl_ =3)) data=newscore;

OUTTREE= Data Set

The OUTTREE= data set contains one observation for each variable clustered plus one observation for each cluster of two or more variables, that is, one observation for each node of the cluster tree. The total number of output observations is between n and 2n-1, where n is the number of variables clustered.

The variables in the OUTTREE= data set are

Chapter Contents
Chapter Contents
Previous
Previous
Next
Next
Top
Top

Copyright © 1999 by SAS Institute Inc., Cary, NC, USA. All rights reserved.