Introduction

Statistical Association is a measure of the relationship between two or more variables. It helps to assess the strength of the relationship between them, determine if the relationship is significant, and determine the direction of the relationship. In Biostatistics, measures of statistical association are used to investigate relationships between variables such as disease risk and exposure, or effect and dose. This article will review some of the most commonly used measures of statistical association for Biostatistics, including Pearson's Correlation Coefficient, Spearman's Correlation Coefficient, and the Odds Ratio.

Pearson's Correlation Coefficient

Pearson’s Correlation Coefficient (also known as the Pearson product-moment correlation coefficient) is a measure of the linear relationship between two variables. It is the most widely used measure of statistical association. The Pearson coefficient ranges from -1 to 1, with -1 indicating a perfect negative linear relationship, 0 indicating no linear relationship, and 1 indicating a perfect positive linear relationship. The Pearson coefficient is typically used when the two variables are continuous and normally distributed.

Spearman's Correlation Coefficient

Spearman’s Correlation Coefficient is a measure of the monotonic relationship between two variables. Unlike the Pearson coefficient, which measures linear relationships, the Spearman coefficient measures relationships that are non-linear. The Spearman coefficient ranges from -1 to 1, with -1 indicating a perfect negative monotonic relationship, 0 indicating no monotonic relationship, and 1 indicating a perfect positive monotonic relationship. The Spearman coefficient is typically used when the two variables are not normally distributed, or when the relationship between the variables is non-linear.

Odds Ratio

The Odds Ratio is a measure of the relative odds of an event occurring. It is used to measure the strength of the association between two variables when one variable is a dichotomous (binary) variable. The Odds Ratio is calculated by dividing the odds of an event occurring for one group by the odds of the event occurring for another group. For example, the Odds Ratio could be used to measure the association between smoking and lung cancer by comparing the odds of a smoker developing lung cancer to the odds of a non-smoker developing lung cancer. The Odds Ratio ranges from 0 to infinity, with 0 indicating no association and higher numbers indicating a stronger association.

Conclusion

In summary, there are several measures of statistical association that can be used to investigate relationships between variables in Biostatistics. The Pearson Correlation Coefficient is used when the two variables are continuous and normally distributed, the Spearman Correlation Coefficient is used when the two variables are not normally distributed or when the relationship between them is non-linear, and the Odds Ratio is used when one of the variables is a dichotomous variable. Each of these measures provides a different view of the relationship between the variables, and can help to assess the strength and direction of the relationship.