Why Use Spearman's Rank Correlation in Epidemiology?
In epidemiological studies, data often do not meet the assumptions required for parametric tests. For example, the relationship between two variables may not be linear, or the data may contain outliers and skewed distributions. Spearman's rank correlation is useful in these cases because it ranks data and thereby reduces the impact of outliers and does not require the data to be normally distributed.
