Confidence Limits of Word Identification Scores Derived Using Nonlinear Quantile Regression

Vijaya K. Narne*, Sören Möller, Anne Wolff, Sabina S. Houmøller, Gérard Loquet, Dorte Hammershøi, Jesper H. Schmidt


Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

32 Downloads (Pure)


The relation between degree of sensorineural hearing loss and maximum speech identification scores (PBmax) is commonly used in audiological diagnosis and rehabilitation. It is important to consider the relation between the degree of hearing loss and the lower boundary of PBmax, as the PBmax varies largely between subjects at a given degree of hearing loss. The present study determines the lower boundary by estimating the lower limit of the one-tailed 95% confidence limit (CL) for a Dantale I, word list, in a large group of young and older subjects with primarily sensorineural hearing loss. PBmax scores were measured using Dantale I, at 30 dB above the speech reception threshold or at the most comfortable level from 1,961 subjects with a wide range of pure-tone averages. A nonlinear quantile regression approach was applied to determine the lower boundary (95% CL) of PBmax scores. At a specific pure-tone average, if the measured PBmax is poorer than the lower boundary (95% CL) of PBmax, it may be considered disproportionately poor.

TidsskriftTrends in Hearing
StatusUdgivet - jan. 2021

Bibliografisk note

Funding Information:
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was primarily funded in part by the Innovation Fund Denmark (Grand Solutions 5164-00011B), Oticon, GN Hearing, and Widex-Sivantos Audiology and partners. The work is supported by all partners (University of Southern Denmark, Aalborg University, Technical University of Denmark, FORCE Technology – Technical-Audiological Laboratory, and Aalborg, Odense, and Copenhagen University Hospitals).

Publisher Copyright:
© The Author(s) 2021.

Copyright 2021 Elsevier B.V., All rights reserved.


Dyk ned i forskningsemnerne om 'Confidence Limits of Word Identification Scores Derived Using Nonlinear Quantile Regression'. Sammen danner de et unikt fingeraftryk.