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
Spearman Rank-Order Correlation
Subsections:
Spearman rank-order correlation is a nonparametric measure of association based on the ranks of the data values. The formula is
where is the rank of , is the rank of , is the mean of the values, and is the mean of the values.
PROC CORR computes the Spearman correlation by ranking the data and using the ranks in the Pearson product-moment correlation formula. In case of ties, the averaged ranks are used.