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Test equality and sample size calculation based on risk difference in a randomized clinical trial with noncompliance
Kung-Jong Lui1, Kuang-Chao Chang
1Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182-7720, USA. kjl@rohan.sdsu.edu
Biometrical Journal. Biometrische Zeitschrift
|February 12, 2008
Summary
This study introduces a new method for sample size calculation in clinical trials, accounting for noncompliance and missing data. The developed formula and test procedure accurately estimate treatment effects among compliant patients.
Area of Science:
- Biostatistics
- Clinical Trials
- Statistical Methodology
Background:
- Noncompliance and missing outcomes in randomized clinical trials (RCTs) can reduce statistical power.
- Accurate sample size calculation is crucial for detecting treatment differences.
Purpose of the Study:
- To develop a sample size calculation formula for RCTs that accounts for noncompliance and missing outcomes.
- To propose a statistical test for comparing treatment effects among compliers.
Main Methods:
- Derivation of the maximum likelihood estimator (MLE) for the risk difference (RD) among compliers.
- Development of an asymptotic test procedure based on the MLE.
- Monte Carlo simulations to evaluate the performance of the test and sample size formula.
Main Results:
- The proposed test procedure and sample size calculation formula perform well.
- The formula accurately accounts for noncompliance and missing outcomes.
- Identified key parameters influencing minimum sample size.
Conclusions:
- The developed methods provide a robust approach for sample size determination in RCTs with noncompliance and missing data.
- The findings support more reliable trial design and analysis.
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