Login / Signup

Reverse graphical approaches for multiple test procedures.

Jiangtao Gou
Published in: Journal of biopharmaceutical statistics (2023)
The graphical approach has been proposed as a general framework for clinical trial designs involving multiple hypotheses, where decisions are made only based on the observed marginal p -values. The graphical approach starts from a graph that includes all hypotheses as vertices and gradually removes some vertices when their corresponding hypotheses are rejected. In this paper, we propose a reverse graphical approach, which starts from a set of singleton graphs and gradually adds vertices into graphs until rejection of a set of hypotheses is made. Proofs of familywise error rate control are provided. A simulation study is conducted for statistical power analysis, and a case study is included to illustrate how the proposed approach can be applied to clinical studies.
Keyphrases
  • clinical trial
  • machine learning
  • study protocol
  • physical activity
  • convolutional neural network
  • double blind
  • neural network
  • phase iii