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Adjusted Inference for Multiple Testing Procedure in Group-Sequential Designs.

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Summary
This summary is machine-generated.

This study introduces adjusted-sequential p-values to control the family-wise error rate (FWER) in group-sequential trials with multiple hypotheses and repeated analyses. These new methods improve statistical rigor for complex clinical trial designs.

Keywords:
adjustedgroup‐sequential designmultiplicitysequentialweighted parametric testing

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Area of Science:

  • Biostatistics
  • Clinical Trials
  • Statistical Inference

Background:

  • Adjusting significance levels for repeated analyses in group-sequential trials is established.
  • Adjusting for multiple hypothesis testing is also well-understood.
  • Simultaneous adjustment for both factors remains under-researched.

Purpose of the Study:

  • To address the gap in statistical methods for group-sequential trials with both repeated analyses and multiple hypothesis testing.
  • To propose novel adjusted-sequential p-values to maintain the family-wise Type I error rate (FWER).

Main Methods:

  • Development of adjusted-sequential p-values for simultaneous control of FWER.
  • Introduction of sequential -values for intersection hypotheses to derive adjusted-sequential -values for elementary hypotheses.
  • Application demonstrated using weighted Bonferroni and weighted parametric tests.

Main Results:

  • Proposed adjusted-sequential p-values provide a method to control FWER under simultaneous multiple testing and repeated analysis.
  • The methodology allows for valid inference on elementary hypotheses within complex sequential trial designs.

Conclusions:

  • The proposed adjusted-sequential p-values offer a statistically sound approach for group-sequential trials involving multiple hypotheses and interim analyses.
  • This work enhances the reliability of statistical decision-making in complex clinical research settings.