  We define a multivariate medial correlation coefficient that extends the
probabilistic interpretation and properties of Blomqvist's $\beta$ coefficient,
incorporates multivariate marginal dependencies and it preserves a stronger
multivariate concordance relation. We determine the maximum and minimum values
attainable and illustrate the results in some models. We end with an
application on real datasets.
