The tail dependence of multivariate distributions is frequently studied via the tool of copulas. This paper develops a general method, which is based on multivariate regular variation, to evaluate the tail dependence of heavy-tailed scale mixtures of multivariate distributions, whose copulas are not explicitly accessible. Tractable formulas for tail dependence parameters are derived, and a sufficient condition under which the parameters are monotone with respect to the heavy-tail index is obtained. The multivariate elliptical distributions are discussed to illustrate the results.