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ERIC Number: EJ1213142
Record Type: Journal
Publication Date: 2019-Mar
Pages: 10
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1092-4388
EISSN: N/A
Available Date: N/A
Bayesian Applications in Auditory Research
McMillan, Garnett P.; Cannon, John B.
Journal of Speech, Language, and Hearing Research, v62 n3 p577-586 Mar 2019
Purpose: This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method: First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors. Working with a few assumptions, including normalcy and conjugacy of prior distribution, we express how one would calculate the posterior distribution using the prior distribution and the likelihood of the parameter. Next, we move to an example in auditory research by considering the effect of sound therapy for reducing the perceived loudness of tinnitus. In this case, as well as most real-world settings, we turn to Markov chain simulations because the assumptions allowing for easy calculations no longer hold. Using Markov chain Monte Carlo methods, we can illustrate several analysis solutions given by a straight forward Bayesian approach. Conclusion: Bayesian methods are widely applicable and can help scientists overcome analysis problems, including how to include existing information, run interim analysis, achieve consensus through measurement, and, most importantly, interpret results correctly.
American Speech-Language-Hearing Association. 2200 Research Blvd #250, Rockville, MD 20850. Tel: 301-296-5700; Fax: 301-296-8580; e-mail: slhr@asha.org; Web site: http://jslhr.pubs.asha.org
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: National Center for Rehabilitative Auditory Research (NCRAR) (VA)
Authoring Institution: N/A
Grant or Contract Numbers: C9230C
Author Affiliations: N/A