  The notion of testing for equivalence of two treatments is widely used in
clinical trials, pharmaceutical experiments,bioequivalence and quality control.
It is essentially approached within the intersection-union (IU) principle.
According to this principle the null hypothesis is stated as the set of effects
lying outside a suitably established interval and the alternative as the set of
effects lying inside that interval. The solutions provided in the literature
are mostly based on likelihood techniques, which in turn are rather difficult
to handle, except for cases lying within the regular exponential family and the
invariance principle. The main goal of present paper is to go beyond most of
the limitations of likelihood based methods, i.e. to work in a nonparametric
setting within the permutation frame. To obtain practical solutions, a new IU
permutation test is presented and discussed. A simple simulation study for
evaluating its main properties, and three application examples are also
presented.
