Measuring Correlation, Association, Reliability and Validity

Learning Objectives

After reading the chapters in this section you should be able to:

  • Compute correlation coefficients using the Pearson Product Moment Correlation Coefficient for continuous data with SAS programming.
  • Compute correlation coefficients using the Spearman Non-Parametric Correlation Coefficient for data based on rankswith SAS programming.
  • Compute the Bland Altman measures of association using specific SAS programming code
  • Evaluate the null hypothesis for a correlation coefficient at p<0.05
  • Compute the Contingency Coefficient based on data from a Chi-square with SAS programming and with the webulators
  • Write SAS programs for each method and review the output that is produced from the computations


The calculation of a correlation coefficient is the method by which a researcher can show a relationship between two measures of interest

This estimate DOES NOT imply cause or causality between the two variables. Rather, the measure is merely an estimate of how closely two variables describe independent responses for a sample. In the following chapters, we will explore the relationship and association between variables using different approaches that include: calculating a Pearson product-moment correlation coefficient, calculating the correlation coefficient with the Non-Parametric Spearman approach based on ranks, calculating measures of association with the methods of Bland and Altman, and calculating the measures of association with chi-square based techniques such as contingency tables and estimates of kappa.


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Applied Statistics in Healthcare Research by William J. Montelpare, Ph.D., Emily Read, Ph.D., Teri McComber, Alyson Mahar, Ph.D., and Krista Ritchie, Ph.D. is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, except where otherwise noted.

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