23: Adjusted Inference for Multiple Testing Procedure in Group-Sequential Designs

Music City Center 

In confirmatory clinical trials that employ multiple testing procedures, rigorous statistical inference is paramount to ensure validity. Two primary approaches exist to control for multiplicity: the first adjusts the significance levels and compares the unadjusted p-values against their corresponding adjusted thresholds, while the second adjusts p-values directly and evaluates them against the prespecified family-wise error rate (FWER). Implementing these methods in group-sequential designs, however, presents unique challenges. This work illustrates their application through examples of Weighted Bonferroni Group Sequential Design (WBGSD) and Weighted Parametric Group Sequential Design (WPGSD), highlighting practical considerations and interpretation.

clinical trial

multiplicity

statistical Inference

group sequential design

adjusted p-value

weighted parametric test 

Biopharmaceutical Section