Confidence Intervals for Ratios of Proportions in Stratified Bilateral Correlated Data
Methodology
2023-03-27 v1
Abstract
Confidence interval (CI) methods for stratified bilateral studies use intraclass correlation to avoid misleading results. In this article, we propose four CI methods (sample-size weighted global MLE-based Wald-type CI, complete MLE-based Wald-type CI, profile likelihood CI, and complete MLE-based score CI) to investigate CIs of proportion ratios to clinical trial design with stratified bilateral data under Dallal's intraclass model. Monte Carlo simulations are performed, and the complete MLE-based score confidence interval (CS) method yields a robust outcome. Lastly, a real data example is conducted to illustrate the proposed four CIs.
Keywords
Cite
@article{arxiv.2303.13557,
title = {Confidence Intervals for Ratios of Proportions in Stratified Bilateral Correlated Data},
author = {Wanqing Tian and Chang-Xing Ma},
journal= {arXiv preprint arXiv:2303.13557},
year = {2023}
}
Comments
arXiv admin note: text overlap with arXiv:2303.12943