title: Properties of multiple intersection-union tests for multiple endpoints in combination therapy trials.
abstract: We consider intersection-union tests involving multiple endpoints in a combination drug trial, for which we control the familywise error rate in the strong sense using closed testing methods. Bonferroni-Holm, Simes-Hommel, and Resampling-Based methods all are considered in this context. Familywise error rate control heuristics are developed and evaluated using a simulation study that is specifically tailored to the intersection-union setting. Both Resampling-Based and Simes-Hommel uniformly outperform the Bonferroni-Holm. Using simulations of power, the choice of Simes-Hommel versus Resampling-Based is seen to depend on the particular alternative of interest. Because it is simpler and has generally good power, we recommend the Simes-Hommel intersection-union tests. The techniques are illustrated using real data from a clinical trial to evaluate a combination asthma therapy.
authors.affiliation: Texas Tech University, Lubbock, USA.
authors.forename: P H
authors.initials: PH
authors.lastname: Westfall
authors.forename: S Y
authors.initials: SY
authors.lastname: Ho
authors.forename: B A
authors.initials: BA
authors.lastname: Prillaman
mesh_terms: D000465:Algorithms; D018927:Anti-Asthmatic Agents / Q000627:therapeutic use; D001249:Asthma / Q000188:drug therapy; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004338:Drug Combinations; D004358:Drug Therapy / Q000706:statistics & numerical data*; D023381:Endpoint Determination / Q000706:statistics & numerical data*; D012107:Research Design
chemical_list: D018927:Anti-Asthmatic Agents; D004338:Drug Combinations