title: Resampling-based methods for the analysis of multiple endpoints in clinical trials.
abstract: We consider multivariate tests for comparing two treatments with multiple endpoints. The test decision is drawn from the simultaneous consideration of the univariate tests for the single endpoints. A general class of these tests, called cut-off tests, can be given, which, however, can lead to highly conservative procedures because the dependencies among the endpoints are not taken into account. In applying resampling-based methods considerable improvements for these tests can be achieved. Resampling-based cut-off tests are proposed which are sensitive against a treatment difference in a single endpoint, in a subgroup of endpoints, or in all endpoints. The results of Monte Carlo simulations demonstrate that a remarkable gain in statistical power as compared to the crude simultaneous consideration can be reached. In particular, for the multivariate one-sided test situation the proposed tests can be recommended. As an example the application of the tests is demonstrated by data from a clinical trial.
authors.affiliation: GSF National Research Center for Environment and Health, Medis-Institut, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany. reitmier@gsf.de
authors.forename: P
authors.initials: P
authors.lastname: Reitmeir
authors.forename: G
authors.initials: G
authors.lastname: Wassmer
mesh_terms: D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D006801:Humans; D009010:Monte Carlo Method; D015999:Multivariate Analysis