Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA.
Ear Hear. 2022;43(5):1447-1455. doi: 10.1097/AUD.0000000000001216. Epub 2022 Mar 16.
Single-ear hearing measurements, such as better-ear, worse-ear or left/right ear, are often used as outcomes in auditory research, yet, measurements in the two ears of the same individual are often strongly but not perfectly correlated. We propose a both-ear method using the Generalized Estimating Equation approach for analysis of correlated binary ear data to evaluate determinants of ear-specific outcomes that includes information from both ears of the same individual.
We first theoretically evaluated bias in odds ratio (OR) estimates based on worse-ear and better-ear hearing outcomes. A simulation study was conducted to compare the finite sample performances of single-ear and both-ear methods in logistic regression models. As an illustrative example, the single-ear and both-ear methods were applied to estimate the association of Dietary Approaches to Stop Hypertension adherence scores with hearing threshold elevation among 3135 women, aged 48 to 68 years, in the Nurses' Health Study II.
Based on statistical theories, the worse-ear and better-ear methods could bias the OR estimates. The simulation results led to the same conclusion. In addition, the simulation results showed that the both-ear method had satisfactory finite sample performance and was more efficient than the single-ear method. In the illustrative example, the confidence intervals of the estimated ORs for the association of Dietary Approaches to Stop Hypertension scores and hearing threshold elevation using the both-ear method were narrower, indicating greater precision, than for those obtained using the other methods.
The worse-ear and better-ear methods may lead to biased estimates, and the left/right ear method typically results in less-efficient estimates. In certain settings, the both-ear method using the Generalized Estimating Equation approach for analyses of audiometric data may be preferable to the single-ear methods.
单耳听力测量，如优耳、差耳或左耳/右耳，通常作为听觉研究的结果，但同一人的双耳测量往往是强相关但不完全相关的。我们提出了一种双耳方法，使用广义估计方程方法分析相关的双耳数据，以评估包括同一个体双耳信息的耳特异性结果的决定因素。
我们首先从理论上评估了基于差耳和优耳听力结果的比值比（OR）估计的偏差。进行了一项模拟研究，比较了单耳和双耳方法在逻辑回归模型中的有限样本性能。作为一个说明性的例子，单耳和双耳方法被应用于估计饮食方法停止高血压（DASH）依从性评分与护士健康研究 II 中 3135 名年龄在 48 至 68 岁的女性听力阈值升高之间的关联。
基于统计理论，差耳和优耳方法可能会偏置 OR 估计值。模拟结果得出了相同的结论。此外，模拟结果表明，双耳方法具有令人满意的有限样本性能，比单耳方法更有效。在说明性示例中，使用双耳方法估计 DASH 评分与听力阈值升高之间的关联的 OR 估计的置信区间比使用其他方法获得的更窄，表明更精确。
差耳和优耳方法可能导致有偏差的估计，而左/右耳方法通常会导致效率较低的估计。在某些情况下，使用广义估计方程方法分析听力数据的双耳方法可能优于单耳方法。
