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Confidence intervals for assessing equivalence of two treatments with combined unilateral and bilateral data
Journal of Applied Statistics ( IF 1.5 ) Pub Date : 2021-07-07 , DOI: 10.1080/02664763.2021.1949440
Shi-Fang Qiu 1 , Ji-Ran Tao 2
Affiliation  

Responses from the paired organs are generally highly correlated in bilateral studies, statistical procedures ignoring the correlation could lead to incorrect results. Note the intraclass correlation in the study of combined unilateral and bilateral outcomes; 11 confidence intervals (CIs) including 7 asymptotic CIs and 4 Bootstrap-resampling CIs for assessing the equivalence of 2 treatments are derived under Rosner's correlated binary data model. Performance is evaluated with respect to the empirical coverage probability (ECP), the empirical coverage width (ECW) and the ratio of the mesial non-coverage probability to the non-coverage probability (RMNCP) via simulation studies. Simulation results show that (i) all CIs except for the Wald CI and the bias-corrected Bootstrap percentile CI generally produce satisfactory ECPs and hence are recommended; (ii) all CIs except for the bias-corrected Bootstrap percentile CI provide preferred RMNCPs and are more symmetrical; (iii) as the measurement of the dependence increases, the ECWs of all CIs except for the score CI and the profile likelihood CI show increasing patterns that look like linear, while there is no obvious pattern on the ECPs of all CIs except for the profile likelihood CI. A data set from an otolaryngologic study is used to illustrate the proposed methods.



中文翻译:

结合单侧和双侧数据评估两种治疗等效性的置信区间

在双边研究中,配对器官的反应通常高度相关,忽略相关性的统计程序可能导致不正确的结果。注意单边和双边联合结果研究中的组内相关性;在 Rosner 的相关二元数据模型下得出 11 个置信区间 (CI),包括 7 个渐近 CI 和 4 个 Bootstrap 重采样 CI,用于评估 2 种治疗的等效性。通过模拟研究,根据经验覆盖概率 (ECP)、经验覆盖宽度 (ECW) 和中间未覆盖概率与未覆盖概率 (RMNCP) 的比率来评估性能。模拟结果表明 (i) 除 Wald CI 和偏差校正的 Bootstrap 百分位数 CI 之外的所有 CI 通常会产生令人满意的 ECP,因此被推荐;(ii) 除偏差校正的 Bootstrap 百分位数 CI 外,所有 CI 均提供首选 RMNCP,并且更加对称;(iii) 随着依赖性测量值的增加,除得分 CI 和轮廓似然 CI 外,所有 CI 的 ECW 均显示出线性增加的模式,而除轮廓外的所有 CI 的 ECP 上没有明显的模式可能性CI。来自耳鼻喉科研究的数据集用于说明所提出的方法。除得分 CI 和轮廓似然 CI 外,所有 CI 的 ECW 均呈现线性增加的模式,而除轮廓似然 CI 外,所有 CI 的 ECP 上没有明显的模式。来自耳鼻喉科研究的数据集用于说明所提出的方法。除得分 CI 和轮廓似然 CI 外,所有 CI 的 ECW 均呈现线性增加的模式,而除轮廓似然 CI 外,所有 CI 的 ECP 上没有明显的模式。来自耳鼻喉科研究的数据集用于说明所提出的方法。

更新日期:2021-07-07
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