A self-designing rule for clinical trials with arbitrary response variables - Joachim Hartung (Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen, 2000)
For testing one-sided but also two-sided hypotheses concerning several treatment arms in group sequentially performed clinical trials with arbitrary outcome variables, a general learning method is considered that allows for a complete self-designing of the study. All information available prior to a stage is used for estimating the sample size and the weight for the next step. In `using up' the variance, the test statistic is built in a bounded finite but random number of stages to test just once the null-hypothesis on rejecting.
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