The Correlations transformation
generates one of the following types of correlation statistics:
The Correlations transformation
is based on the CORR procedure, which is documented in the
Base SAS Procedures Guide: Statistical Procedures. The
CORR procedure computes Pearson correlation coefficients, three nonparametric
measures of association, and the probabilities associated with these
statistics. The correlation statistics include the following:

Pearson productmoment correlation

Spearman rankorder correlation

Kendall's taub coefficient

Hoeffding's measure of dependence,
D

Pearson, Spearman, and Kendall
partial correlation
Pearson productmoment correlation is a parametric
measure of a linear relationship between two variables. For nonparametric
measures of association, Spearman rankorder correlation uses the
ranks of the data values and Kendall's taub uses the number of concordances
and discordances in paired observations. Hoeffding's measure of dependence
is another nonparametric measure of association that detects more
general departures from independence. A partial correlation provides
a measure of the correlation between two variables after controlling
the effects of other variables.
You can specify which
columns are correlated and which columns are analyzed. You can group
rows in the output based on the values in specified grouping columns.
Output appears in a target table or in the
Output tab in the process designer. ODS output in the form of HTML, PDF,
or RTF can also be sent to a folder on the SAS Application Server
that executes the job or to any folder that is accessible to that
SAS Application Server.
The target receives
data only for the source columns that are involved in the correlation.
The target requires two columns that the Correlations transformation
populates: _TYPE_ specifies the type of the statistic and _NAME_ identifies
the correlation column.
The Correlations transformation
requires that grouping columns be sorted in ascending order in the
source. If you specify grouping columns, you can sort those columns
before the Correlations transformation by using a SAS Sort transformation.