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Sequential monitoring of randomization tests: stratified randomization
Yanqiong Zhang1, William F Rosenberger, Robert T Smythe
1Merck & Co., Ry34-A316, P.O. Box 2000, Rahway, New Jersey 07065-0900, USA. yanqiong_zhang@merck.com
Biometrics
|September 11, 2007
Summary
This study introduces sequential monitoring plans for clinical trials using randomization-based inference. It defines and calculates the information fraction for permuted block, stratified block, and stratified urn designs.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Statistical Inference
Background:
- Sequential monitoring plans are crucial for early stopping of clinical trials based on efficacy.
- Randomization-based inference is a key component in ensuring unbiased trial results.
- Various designs like permuted block, stratified block, and stratified urn are used in clinical trials.
Purpose of the Study:
- To establish sequential monitoring plans for randomization-based inference.
- To define and discuss the calculation of the information fraction for specific trial designs.
Main Methods:
- Setting up sequential monitoring plans for permuted block designs.
- Developing sequential monitoring plans for stratified block designs.
- Implementing sequential monitoring plans for stratified urn designs.
- Proposing a definition for information fraction in these contexts.
Main Results:
- Successfully established sequential monitoring plans for the specified designs.
- Defined a novel information fraction applicable to these randomization-based inference settings.
- Demonstrated methods for calculating the information fraction across different designs.
Conclusions:
- Sequential monitoring plans can be effectively implemented within randomization-based inference frameworks.
- The proposed information fraction provides a standardized measure for interim analyses.
- This work facilitates more efficient and ethical clinical trial conduct through early stopping rules.
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Simple randomization
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Simple randomization
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