  In clinical trials the comparison of two different populations is a
frequently addressed problem. Non-linear (parametric) regression models are
commonly used to describe the relationship between covariates as the dose and a
response variable in the two groups. In some situations it is reasonable to
assume some model parameters to be the same, for instance the placebo effect or
the maximum treatment effect. In this paper we develop a (parametric) bootstrap
test to establish the similarity of two regression curves sharing some common
parameters. We show by theoretical arguments and by means of a simulation study
that the new test controls its level and achieves a reasonable power. Moreover,
it is demonstrated that under the assumption of common parameters a
considerable more powerful test can be constructed compared to the test which
does not use this assumption. Finally, we illustrate potential applications of
the new methodology by a clinical trial example.
