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Related Experiment Video

Updated: Jan 26, 2026

Ultrasound Images of the Tongue: A Tutorial for Assessment and Remediation of Speech Sound Errors
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The Evolution of Statistical Methods in Speech, Language, and Hearing Sciences.

Jacob J Oleson1, Grant D Brown1, Ryan McCreery2

  • 1Department of Biostatistics, University of Iowa, Iowa City.

Journal of Speech, Language, and Hearing Research : JSLHR
|April 6, 2019
PubMed
Summary
This summary is machine-generated.

Traditional statistical methods often fail for speech and hearing science data. This review highlights advanced statistical techniques, including Bayesian methods and statistical learning, to better analyze complex communication science data.

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Area of Science:

  • Speech, language, and hearing sciences
  • Communication sciences and disorders

Background:

  • Traditional statistical methods often have assumptions not met by communication science data.
  • Behavioral data in speech and hearing research frequently violate standard statistical assumptions.

Purpose of the Study:

  • To review underutilized statistical methods applicable to speech, language, and hearing sciences.
  • To provide guidance on alternative statistical approaches for complex communication data.

Main Methods:

  • Review of advanced statistical techniques.
  • Identification of methods for proportion and repeated measures data.
  • Introduction to Bayesian inference and statistical learning.

Main Results:

  • Alternative statistical approaches can be advantageous for proportion and repeated measures data.
  • Bayesian methods and statistical learning offer powerful tools for complex analyses.
  • Modern statistical techniques enhance data analysis flexibility.

Conclusions:

  • Advanced statistical methods offer greater flexibility for communication scientists.
  • These techniques enable more direct and informative research questions in the field.
  • Utilizing modern statistics can lead to deeper insights in speech and hearing research.