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Interval estimation of proportion ratios for stratified bilateral correlated binary data.
1Department of Biostatistics, University at Buffalo, Buffalo, NY, USA.
Statistical Methods in Medical Research
|October 18, 2019
Summary
New confidence interval (CI) methods for correlated bilateral data in clinical trials are presented. The complete score (CS) statistics method is recommended for its reliable performance in comparative studies.
Area of Science:
- Biostatistics
- Clinical Trials
- Medical Statistics
Background:
- Comparative clinical trials often involve bilateral binary data, where measurements are taken on both sides of a subject.
- Correlated data structures in bilateral binary outcomes require specialized statistical methods for accurate analysis.
- Existing confidence interval (CI) methods may not adequately address the complexities of correlated bilateral binary data.
Purpose of the Study:
- To construct and evaluate novel confidence interval (CI) methods for the ratio of two proportions with correlated bilateral binary data.
- To assess the performance of these CIs using simulations, focusing on mean coverage probability (MCP), mean interval width (MIW), and the ratio of mesial non-coverage probability to the distal non-coverage probability (RMNCP).
- To recommend a robust CI method for general application in stratified comparative clinical trials.
Main Methods:
- Development of new confidence interval (CI) methods tailored for the ratio of two proportions.
- Application to correlated bilateral binary data within a stratified clinical trial design.
- Performance evaluation through Monte Carlo simulations assessing MCP, MIW, and RMNCP.
Main Results:
- The proposed CI methods were evaluated based on their statistical performance metrics.
- Empirical results indicated that the CI method based on complete score (CS) statistics demonstrated favorable performance across the evaluated criteria.
- The CS method showed robustness in handling correlated bilateral binary data.
Conclusions:
- The confidence interval method utilizing complete score (CS) statistics is recommended for general application in comparative clinical trials with correlated bilateral binary data.
- This method provides reliable estimation for the ratio of two proportions in such settings.
- The study provides a practical tool for biostatisticians and researchers analyzing complex clinical trial data.
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