Abstract
Confidence interval (CI) methods for the ratio of two proportions in the presence of correlated bilateral binary data are constructed for comparative clinical trials with stratified design. Simulations are conducted to evaluate the performance of the presented CIs with respect to mean coverage probability (MCP), mean interval width (MIW), and the ratio of mesial non-coverage probability to the distal non-coverage probability (RMNCP). Based on the empirical results, we suggest the use of the proposed CI method based on the complete score statistics (CS) for general applications. An example from a rheumatology study is used to demonstrate the proposed methodologies.
| Original language | English |
|---|---|
| Pages (from-to) | 1987-2014 |
| Number of pages | 28 |
| Journal | Statistical Methods in Medical Research |
| Volume | 29 |
| Issue number | 7 |
| DOIs | |
| State | Published - Jul 1 2020 |
Keywords
- Correlated binary data
- Rosner’s constant R model
- score-based confidence interval
- stratified bilateral-sample design
Fingerprint
Dive into the research topics of 'Interval estimation of proportion ratios for stratified bilateral correlated binary data'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver