Measures of Association

The measures of association refer to a wide variety of coefficients (including bivariate correlation and regression coefficients) that measure the strength and direction of the relationship between variables; these measures of strength, or association, can be described in several ways, depending on the analysis.

There are certain points that a researcher should know in order to better understand the measures of statistical association.

  • First, the researcher should know that measures of association are not the same as measures of statistical significance.  It is possible for a weak association to be statistically significant; it is also possible for a strong association to not be statistically significant.
  • For measures of association, a value of zero signifies that no relationship exists.  In a correlation analysis, if the coefficient (r) has a value of one, it signifies a perfect relationship on the variables of interest. In regression analyses, if the standardized beta weight (β) has a value of one, it also signifies a perfect relationship on the variables of interest.  The researcher should note that bivariate measures of association (e.g., Pearson correlations) are inappropriate for curvilinear relationships or discontinuous relationships.
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