Unlike other measures of correlation, Kendall's Tau does not assume a normal distribution of the data, making it more robust for analyzing data that are not normally distributed. This is especially important in epidemiological studies where data can often be skewed or ordinal in nature. It is also less sensitive to outliers, providing a more accurate picture of the association between variables.
