Both-Ear Method for the Analysis of Audiometric Data

Objective: 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. Design: 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. Results: 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. Conclusions: 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.