Rank correlation under categorical confounding

Correspondence: [email protected] Department of Decision Sciences, HEC Montréal, 3000 chemin de la Côte-Sainte-Catherine, H3T 2A7 Montréal, Canada Abstract Rank correlation is invariant to bijective marginal transformations, but it is not immune to confounding. Assuming a categorical confounding variable is observed, the author proposes weighted coefficients of correlation for continuous variables developed within a larger framework based on copulas. While the weighting is clear under the assumption that the dependence is the same within each group implied by the confounder, the author extends the Minimum Averaged Mean Squared Error (MAMSE) weights to borrow strength between groups when the dependence may vary across them. Asymptotic properties of the proposed coefficients are derived and simulations are used to assess their finite sample properties.