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Confidence Intervals for Ratios of Proportions in Stratified Bilateral Correlated Data

2023/03/23 by Tian, Wanqing, Ma, Chang-Xing · 1 citation
#FOS: Computer and information sciences #Methodology (stat.ME)

paper · doi:10.48550/arxiv.2303.13557

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.

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