Which statistical measure uses ranked values to examine the relationship between two ordinal variables?

The Spearman correlation is a non-parametric measure that uses ranked values to assess the strength and direction of the relationship between two ordinal variables. By converting raw scores into ranks, Spearman's method is particularly useful for analyzing data that may not meet the assumptions necessary for parametric tests, such as normal distribution.

This method focuses on the relative position of data points rather than their specific values, making it ideal for ordinal variables where the differences between ranks may not be uniform. It effectively captures the monotonic relationship between the variables, indicating whether, as one variable increases, the other tends to increase as well (or decrease).

Other measures like Pearson correlation require interval or ratio data and assume a linear relationship between the variables, while Kendall’s tau similarly addresses ordinal data but uses a different formula based on the ranks' concordance and discordance. Regression analysis, on the other hand, focuses on predicting the outcome of one variable based on another and is not limited to ordinal data.