title: Multiple contrast tests for multiple endpoints in the presence of heteroscedasticity.
abstract: This article describes an extension of multiple contrast tests to the case of multiple, correlated endpoints. These endpoints are assumed to be normally distributed with different scales and variances. Unlike in previous articles, the covariance matrices are also assumed to be unequal for the treatment groups. Approximate multivariate t-distributions are used to obtain multiplicity-adjusted p-values and quantiles for test decisions or simultaneous confidence intervals. Simulation results show that this approach controls the family-wise error type I over both the comparisons and the endpoints in an admissible range. The approach will be applied to a semi-synthetic example data set of a randomized, placebo-controlled phase IIb dose-finding study of a novel anti-muscarinic agent for five continuous endpoints. A related R package is available.
authors: Mario
authors: M
authors: Hasler
mesh_terms: D017322:Clinical Trials, Phase II as Topic / Q000379:methods*; D003198:Computer Simulation; D016001:Confidence Intervals; D003627:Data Interpretation, Statistical; D004305:Dose-Response Relationship, Drug; D023381:Endpoint Determination / Q000379:methods*; D006801:Humans; D018727:Muscarinic Antagonists / Q000008:administration & dosage / Q000494:pharmacology; D016032:Randomized Controlled Trials as Topic / Q000379:methods*; D014549:Urinary Incontinence / Q000188:drug therapy
chemical_list: D018727:Muscarinic Antagonists