The CORR Procedure 
PROC CORR Statement 
Option 
Description 

Data Sets 

DATA= 
Specifies the input data set 
OUTH= 
Specifies the output data set with Hoeffding’s statistics 
OUTK= 
Specifies the output data set with Kendall correlation statistics 
OUTP= 
Specifies the output data set with Pearson correlation statistics 
OUTS= 
Specifies the output data set with Spearman correlation statistics 
Statistical Analysis 

EXCLNPWGT 
Excludes observations with nonpositive weight values from the analysis 
FISHER 
Requests correlation statistics using Fisher’s transformation 
HOEFFDING 
Requests Hoeffding’s measure of dependence, 
KENDALL 
Requests Kendall’s taub 
NOMISS 
Excludes observations with missing analysis values from the analysis 
PEARSON 
Requests Pearson productmoment correlation 
SPEARMAN 
Requests Spearman rankorder correlation 
Pearson Correlation Statistics 

ALPHA 
Computes Cronbach’s coefficient alpha 
COV 
Computes covariances 
CSSCP 
Computes corrected sums of squares and crossproducts 
FISHER 
Computes correlation statistics based on Fisher’s transformation 
SINGULAR= 
Specifies the singularity criterion 
SSCP 
Computes sums of squares and crossproducts 
VARDEF= 
Specifies the divisor for variance calculations 
ODS Output Graphics 

PLOTS=MATRIX 
Displays the scatter plot matrix 
PLOTS=SCATTER 
Displays scatter plots for pairs of variables 
Printed Output 

BEST= 
Displays the specified number of ordered correlation coefficients 
NOCORR 
Suppresses Pearson correlations 
NOPRINT 
Suppresses all printed output 
NOPROB 
Suppresses values 
NOSIMPLE 
Suppresses descriptive statistics 
RANK 
Displays ordered correlation coefficients 
The following options can be used in the PROC CORR statement. They are listed in alphabetical order.
calculates and prints Cronbach’s coefficient alpha. PROC CORR computes separate coefficients using raw and standardized values (scaling the variables to a unit variance of 1). For each VAR statement variable, PROC CORR computes the correlation between the variable and the total of the remaining variables. It also computes Cronbach’s coefficient alpha by using only the remaining variables.
If a WITH statement is specified, the ALPHA option is invalid. When you specify the ALPHA option, the Pearson correlations will also be displayed. If you specify the OUTP= option, the output data set also contains observations with Cronbach’s coefficient alpha. If you use the PARTIAL statement, PROC CORR calculates Cronbach’s coefficient alpha for partialled variables. See the section Partial Correlation for details.
prints the highest correlation coefficients for each variable, . Correlations are ordered from highest to lowest in absolute value. Otherwise, PROC CORR prints correlations in a rectangular table, using the variable names as row and column labels.
If you specify the HOEFFDING option, PROC CORR displays the statistics in order from highest to lowest.
displays the variance and covariance matrix. When you specify the COV option, the Pearson correlations will also be displayed. If you specify the OUTP= option, the output data set also contains the covariance matrix with the corresponding _TYPE_ variable value 'COV.' If you use the PARTIAL statement, PROC CORR computes a partial covariance matrix.
displays a table of the corrected sums of squares and crossproducts. When you specify the CSSCP option, the Pearson correlations will also be displayed. If you specify the OUTP= option, the output data set also contains a CSSCP matrix with the corresponding _TYPE_ variable value 'CSSCP.' If you use a PARTIAL statement, PROC CORR prints both an unpartial and a partial CSSCP matrix, and the output data set contains a partial CSSCP matrix.
names the SAS data set to be analyzed by PROC CORR. By default, the procedure uses the most recently created SAS data set.
excludes observations with nonpositive weight values from the analysis. By default, PROC CORR treats observations with negative weights like those with zero weights and counts them in the total number of observations.
requests confidence limits and values under a specified null hypothesis, , for correlation coefficients by using Fisher’s transformation. These correlations include the Pearson correlations and Spearman correlations.
The following fisheroptions are available:
specifies the level of the confidence limits for the correlation, . The value of the ALPHA= option must be between 0 and 1, and the default is ALPHA=0.05.
specifies whether or not the bias adjustment is used in constructing confidence limits. The BIASADJ=YES option also produces a new correlation estimate that uses the bias adjustment. By default, BIASADJ=YES.
specifies the value in the null hypothesis , where . By default, RHO0=0.
specifies the type of confidence limits. The TYPE=LOWER option requests a lower confidence limit from the lower alternative , the TYPE=UPPER option requests an upper confidence limit from the upper alternative , and the default TYPE=TWOSIDED option requests twosided confidence limits from the twosided alternative .
requests a table of Hoeffding’s statistics. This statistic is 30 times larger than the usual definition and scales the range between 0.5 and 1 so that large positive values indicate dependence. The HOEFFDING option is invalid if a WEIGHT or PARTIAL statement is used.
requests a table of Kendall’s taub coefficients based on the number of concordant and discordant pairs of observations. Kendall’s taub ranges from 1 to 1.
The KENDALL option is invalid if a WEIGHT statement is used. If you use a PARTIAL statement, probability values for Kendall’s partial taub are not available.
suppresses displaying of Pearson correlations. If you specify the OUTP= option, the data set type remains CORR. To change the data set type to COV, CSSCP, or SSCP, use the TYPE= data set option.
excludes observations with missing values from the analysis. Otherwise, PROC CORR computes correlation statistics by using all of the nonmissing pairs of variables. Using the NOMISS option is computationally more efficient.
suppresses all displayed output, which also includes output produced with ODS Graphics. Use the NOPRINT option if you want to create an output data set only.
suppresses displaying the probabilities associated with each correlation coefficient.
suppresses printing simple descriptive statistics for each variable. However, if you request an output data set, the output data set still contains simple descriptive statistics for the variables.
creates an output data set containing Hoeffding’s statistics. The contents of the output data set are similar to those of the OUTP= data set. When you specify the OUTH= option, the Hoeffding’s statistics will be displayed.
creates an output data set containing Kendall correlation statistics. The contents of the output data set are similar to those of the OUTP= data set. When you specify the OUTK= option, the Kendall correlation statistics will be displayed.
creates an output data set containing Pearson correlation statistics. This data set also includes means, standard deviations, and the number of observations. The value of the _TYPE_ variable is 'CORR.' When you specify the OUTP= option, the Pearson correlations will also be displayed. If you specify the ALPHA option, the output data set also contains six observations with Cronbach’s coefficient alpha.
creates an output data set containing Spearman correlation coefficients. The contents of the output data set are similar to those of the OUTP= data set. When you specify the OUTS= option, the Spearman correlation coefficients will be displayed.
requests a table of Pearson productmoment correlations. The correlations range from 1 to 1. If you do not specify the HOEFFDING, KENDALL, SPEARMAN, OUTH=, OUTK=, or OUTS= option, the CORR procedure produces Pearson productmoment correlations by default. Otherwise, you must specify the PEARSON, ALPHA, COV, CSSCP, SSCP, or OUT= option for Pearson correlations. Also, if a scatter plot or a scatter plot matrix is requested, the Pearson correlations will be displayed.
requests statistical graphics via the Output Delivery System (ODS). To request these graphs, you must specify the ODS GRAPHICS ON statement in addition to the following options in the PROC CORR statement. For more information about the ODS GRAPHICS statement, see Chapter 21, Statistical Graphics Using ODS (SAS/STAT 9.22 User's Guide).
The global plot option ONLY suppresses the default plots, and only plots specifically requested are displayed. The plot request options include the following:
requests a scatter plot matrix for variables. That is, the procedure displays a symmetric matrix plot with variables in the VAR list if a WITH statement is not specified. Otherwise, the procedure displays a rectangular matrix plot with the WITH variables appearing down the side and the VAR variables appearing across the top.
requests scatter plots for pairs of variables. That is, the procedure displays a scatter plot for each applicable pair of distinct variables from the VAR list if a WITH statement is not specified. Otherwise, the procedure displays a scatter plot for each applicable pair of variables, one from the WITH list and the other from the VAR list.
By default, PLOTS=MATRIX, a scatter plot matrix for all variables is displayed. When a scatter plot or a scatter plot matrix is requested, the Pearson correlations will also be displayed.
The available matrixoptions are as follows:
displays histograms of variables in the VAR list in the symmetric matrix plot.
specifies the maximum number of variables in the VAR list to be displayed in the matrix plot, where . The NVAR=ALL option uses all variables in the VAR list. By default, NVAR=5.
specifies the maximum number of variables in the WITH list to be displayed in the matrix plot, where . The NWITH=ALL option uses all variables in the WITH list. By default, NWITH=5.
The available scatteroptions are as follows:
specifies the values for the confidence or prediction ellipses to be displayed in the scatter plots, where . For each value specified, a () confidence or prediction ellipse is created. By default, .
requests prediction ellipses for new observations (ELLIPSE=PREDICTION), confidence ellipses for the mean (ELLIPSE=CONFIDENCE), or no ellipses (ELLIPSE=NONE) to be created in the scatter plots. By default, ELLIPSE=PREDICTION.
suppresses the default inset of summary information for the scatter plot. The inset table contains the number of observations (Observations) and correlation.
specifies the maximum number of variables in the VAR list to be displayed in the plots, where . The NVAR=ALL option uses all variables in the VAR list. By default, NVAR=5.
specifies the maximum number of variables in the WITH list to be displayed in the plots, where . The NWITH=ALL option uses all variables in the WITH list. By default, NWITH=5.
displays the ordered correlation coefficients for each variable. Correlations are ordered from highest to lowest in absolute value. If you specify the HOEFFDING option, the statistics are displayed in order from highest to lowest.
specifies the criterion for determining the singularity of a variable if you use a PARTIAL statement. A variable is considered singular if its corresponding diagonal element after Cholesky decomposition has a value less than p times the original unpartialled value of that variable. The default value is 1E8. The range of is between 0 and 1.
requests a table of Spearman correlation coefficients based on the ranks of the variables. The correlations range from 1 to 1. If you specify a WEIGHT statement, the SPEARMAN option is invalid.
displays a table of the sums of squares and crossproducts. When you specify the SSCP option, the Pearson correlations will also be displayed. If you specify the OUTP= option, the output data set contains a SSCP matrix and the corresponding _TYPE_ variable value is 'SSCP.' If you use a PARTIAL statement, the unpartial SSCP matrix is displayed, and the output data set does not contain an SSCP matrix.
specifies the variance divisor in the calculation of variances and covariances. The default is VARDEF=DF.
Table 2.2 displays available values and associated divisors for the VARDEF= option, where n is the number of nonmissing observations, k is the number of variables specified in the PARTIAL statement, and is the weight associated with the th nonmissing observation.
Value 
Description 
Divisor 

DF 
degrees of freedom 

N 
number of observations 

WDF 
sum of weights minus one 

WEIGHT  WGT 
sum of weights 

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