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Properties of simple randomization in clinical trials.
1George Washington University, Department of Statistics/Computer and Information Systems, Rockville, Maryland 20852.
Controlled Clinical Trials
|December 1, 1988
Summary
Complete randomization, like a coin toss, is ideal for large clinical trials. It minimizes selection and accidental bias, ensuring reliable treatment effect estimates.
Area of Science:
- Biostatistics
- Clinical Trial Design
- Statistical Inference
Background:
- Randomization is crucial for unbiased clinical trials.
- Complete randomization (e.g., coin toss) and random allocation rules (e.g., random permutation) are common methods.
- Understanding their properties is essential for robust trial design.
Purpose of the Study:
- To compare the properties of complete randomization and the random allocation rule.
- To assess their impact on treatment imbalances, statistical power, and bias.
- To evaluate their suitability for large clinical trials.
Main Methods:
- Analysis of treatment imbalance likelihood for both methods.
- Computation of large-sample permutational distributions for linear rank tests.
- Application of Blackwell-Hodges and Efron models to assess selection and accidental bias.
Main Results:
- Treatment imbalances are negligible in large trials (n>200) for both methods.
- Complete randomization eliminates selection bias, while the random allocation rule has potential for it.
- Complete randomization minimizes accidental bias in finite samples.
Conclusions:
- Complete randomization is advantageous in large clinical trials due to its superior bias control.
- Both methods are asymptotically equivalent, but complete randomization offers better protection against bias for finite sample sizes.
- The choice of randomization method impacts trial integrity and reliability.