Accuracy and Consistency of Confidence Limits for Monosyllable Identification Scores Derived Using Simulation, the...

Audiological diagnosis and rehabilitation often involve the assessment of whether the maximum speech identification score (PB_max) is poorer than expected from the pure-tone average (PTA) threshold. This requires the estimation of the lower boundary of the PB_max values expected for a given PTA (one-tailed 95% confidence limit, CL). This study compares the accuracy and consistency of three methods for estimating the 95% CL.

The 95% CL values were estimated using a simulation method, the Harrell-Davis (HD) estimator, and non-linear quantile regression (nQR); the latter two are both distribution-free methods. The first two methods require the formation of sub-groups with different PTAs. Accuracy and consistency in the estimation of the 95% CL were assessed by applying each method to many random samples of 50% of the available data and using the fitted parameters to predict the data for the remaining 50%.

A total of 642 participants aged 17 to 84 years with sensorineural hearing loss were recruited from audiology clinics. Pure-tone audiograms were obtained and PB_max scores were measured using monosyllables at 40 dB above the speech recognition threshold or at the most comfortable level.

For the simulation method, 6.7 to 8.2% of the PB_max values fell below the 95% CL for both ears, exceeding the target value of 5%. For the HD and nQR methods, the PB_max values fell below the estimated 95% CL for approximately 5% of the ears, indicating good accuracy. Consistency, estimated from the standard deviation of the deviations from the target value of 5%, was similar for all the methods.

The nQR method is recommended because it has good accuracy and consistency, and it does not require the formation of arbitrary PTA sub-groups.