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ERIC Number: EJ1217434
Record Type: Journal
Publication Date: 2019-May
Pages: 18
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1092-4388
EISSN: N/A
An Introduction to Bayesian Multilevel Models Using brms: A Case Study of Gender Effects on Vowel Variability in Standard Indonesian
Nalborczyk, Ladislas; Batailler, Cédric; Lœvenbruck, Hélène; Vilain, Anne; Bürkner, Paul-Christian
Journal of Speech, Language, and Hearing Research, v62 n5 p1225-1242 May 2019
Purpose: Bayesian multilevel models are increasingly used to overcome the limitations of frequentist approaches in the analysis of complex structured data. This tutorial introduces Bayesian multilevel modeling for the specific analysis of speech data, using the brms package developed in R. Method: In this tutorial, we provide a practical introduction to Bayesian multilevel modeling by reanalyzing a phonetic data set containing formant (F1 and F2) values for 5 vowels of standard Indonesian (ISO 639-3:ind), as spoken by 8 speakers (4 females and 4 males), with several repetitions of each vowel. Results: We first give an introductory overview of the Bayesian framework and multilevel modeling. We then show how Bayesian multilevel models can be fitted using the probabilistic programming language Stan and the R package brms, which provides an intuitive formula syntax. Conclusions: Through this tutorial, we demonstrate some of the advantages of the Bayesian framework for statistical modeling and provide a detailed case study, with complete source code for full reproducibility of the analyses (https://osf.io/dpzcb/).
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: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A