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Graphical approaches for the control of generalized error rates
David S Robertson1, James M S Wason1,2, Frank Bretz3,4
1MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.
Statistics in Medicine
|June 20, 2020
Summary
This study extends graphical methods to control generalized error rates beyond the familywise error rate (FWER) in clinical trials. New procedures offer increased power for multiple hypothesis testing in exploratory settings.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Statistical Inference
Background:
- Confirmatory clinical trials typically control the familywise error rate (FWER) to bound false rejections.
- Hierarchical hypothesis structures are common, reflecting clinical importance.
- The graphical approach effectively controls FWER for complex objectives.
Purpose of the Study:
- To extend graphical methods for controlling generalized error rates in clinical trials.
- To address limitations of FWER control, especially in exploratory settings with many hypotheses.
- To introduce methods for controlling the k-FWER and False Discovery Proportion (FDP) tail probability.
Main Methods:
- Adaptation of the graphical approach for generalized error rate control.
- Development of procedures for controlling the k-FWER (probability of k or more false rejections).
- Incorporation of asymptotic control for the False Discovery Rate (FDR).
Main Results:
- Demonstration of graphical procedures for controlling generalized error rates.
- Extension of existing graphical methods to new error metrics.
- Successful application of developed procedures in three clinical trial case studies.
Conclusions:
- Graphical methods can be extended to control generalized error rates, enhancing statistical power.
- These extended methods are valuable for exploratory clinical trials with multiple hypotheses.
- The demonstrated procedures offer flexible and powerful tools for modern clinical trial design.
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