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A Structural Equation Approach to Characterizing Growth and Nonlinearity Underlying Distortion Product Otoacoustic Emissions
Journal article   Open access   Peer reviewed

A Structural Equation Approach to Characterizing Growth and Nonlinearity Underlying Distortion Product Otoacoustic Emissions

Shawn S Goodman, M Ehsan Khalili, Julia H Roemen, Ishan Bhatt, Skyler G Jennings, Jeffery T Lichtenhan and Sumitrajit Dhar
Journal of the Association for Research in Otolaryngology
06/15/2026
DOI: 10.1007/s10162-026-01057-9
PMID: 42298225
url
https://doi.org/10.1007/s10162-026-01057-9View
Published (Version of record) Open Access

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Abstract

Distortion product otoacoustic emission (DPOAE) magnitudes measured in the ear canal in response to a range of primary stimulus levels as growth functions (GFs) may be useful for assessing cochlear non-linearity, predicting behavioral audiometric thresholds, estimating loudness perception, and differentiating types of cochlear pathology. A variety of stimulation schemes have been proposed, and GF shapes differ depending on the stimulation scheme used. A clearer understanding of the relationships between stimuli, GFs, cochlear non-linearities, and cochlear health is important for maximizing the diagnostic potential of DPOAEs. Latent growth modeling, a technique within the structural equation modeling framework, can provide insight into the relationships between observed (e.g., GFs) and unobserved latent variables (e.g., cochlear non-linearities). We describe a latent growth model for characterizing GFs with a generalized logistic function representing the latent non-linearity, coupled with a generalized linear regression model appropriate for fitting GFs with varying signal-to-noise ratios (SNRs). The model was applied to GF data from twelve young adult ears (9 female, 3 male). The resulting fits inferred the shape of the underlying non-linearity and also quantified standard GF characteristics such as slope, threshold, and inflection points. Data from participants, along with Monte Carlo simulations, demonstrate that this fitting method performs well under low SNR conditions and accurately predicts DPOAE magnitudes at low stimulus levels. This report establishes a robust method for characterizing GFs, supporting the long-term goal of applying the method in future studies of the relationships between acoustic stimuli, GFs, cochlear non-linearities, and cochlear health.
 Latent growth curve analysis Rician Generalized linear regression Latent growth model Structural equation model Input–output

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