![]() Resulting in 6 hypotheses to be tested in the trial. Testing, 3) carrying out hypothesis testing, and 4) verification of theįor the template example, there are 3 endpoints and 2 populations Results entry which includes event counts and nominal p-values for In short, we begin with 1) design specification followed by 2) The table of contents above lays out the organization of theĭocument. Updated group sequential bounds for each hypothesis at the largestĪlpha-level it was evaluated can be checked vs. nominal p-values at eachĪnalysis to verify the testing conclusions reached with the above.The final Type I error available for testing each hypothesis that was The final graph, assuming not all hypotheses were rejected, provides.Single hypothesis rejected from the previous graph. Multiplicity graph, followed by updated multiplicity graphs, each with a The graphical testing produces a sequence including the original.Plugged into standard graphical hypothesis testing R package, The initial testing is done by using sequential p-values (Liu and Anderson 2008) which can then be.Provide methods to check hypothesis testing. Given the complexity involved, substantial effort has been taken to Verifiable conclusion in multiple trials such as Burtness et al. This hasīeen found to be particularly valuable to provide a prompt and Way that is meant to be re-used in a straightforward fashion. GsDesign packages is non-trivial, but developed in a Many details building on the necessarily simple example provided by In particular, weĭemonstrate design and analysis of a complex oncology trial. Graphical multiplicity control when used with group sequential design This document is intended to evaluate statistical significance for
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