The CORR Procedure
- Overview
- Getting Started
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Syntax
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DetailsPearson Product-Moment CorrelationSpearman Rank-Order CorrelationKendall’s Tau-b Correlation CoefficientHoeffding Dependence CoefficientPartial CorrelationFisher’s z TransformationPolychoric CorrelationPolyserial CorrelationCronbach’s Coefficient AlphaConfidence and Prediction EllipsesMissing ValuesIn-Database ComputationOutput TablesOutput Data SetsODS Table NamesODS Graphics
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ExamplesComputing Four Measures of AssociationComputing Correlations between Two Sets of VariablesAnalysis Using Fisher’s z TransformationApplications of Fisher’s z TransformationComputing Polyserial CorrelationsComputing Cronbach’s Coefficient AlphaSaving Correlations in an Output Data SetCreating Scatter PlotsComputing Partial Correlations
- References
Output Tables
By default, PROC CORR prints a report that includes descriptive statistics and correlation statistics for each variable. The descriptive statistics include the number of observations with nonmissing values, the mean, the standard deviation, the minimum, and the maximum.
If a nonparametric measure of association is requested, the descriptive statistics include the median. Otherwise, the sample sum is included. If a Pearson partial correlation is requested, the descriptive statistics also include the partial variance and partial standard deviation.
If variable labels are available, PROC CORR labels the variables. If you specify the CSSCP, SSCP, or COV option, the appropriate sums of squares and crossproducts and covariance matrix appear at the top of the correlation report. If the data set contains missing values, PROC CORR prints additional statistics for each pair of variables. These statistics, calculated from the observations with nonmissing row and column variable values, might include the following:
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SSCP(’W’,’V’), uncorrected sums of squares and crossproducts
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USS(’W’), uncorrected sums of squares for the row variable
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USS(’V’), uncorrected sums of squares for the column variable
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CSSCP(’W’,’V’), corrected sums of squares and crossproducts
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CSS(’W’), corrected sums of squares for the row variable
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CSS(’V’), corrected sums of squares for the column variable
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COV(’W’,’V’), covariance
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VAR(’W’), variance for the row variable
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VAR(’V’), variance for the column variable
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DF(’W’,’V’), divisor for calculating covariance and variances
For each pair of variables, PROC CORR prints the correlation coefficients, the number of observations used to calculate the coefficient, and the p-value.
If you specify the ALPHA option, PROC CORR prints Cronbach’s coefficient alpha, the correlation between the variable and the total of the remaining variables, and Cronbach’s coefficient alpha by using the remaining variables for the raw variables and the standardized variables.