# 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.