An Introduction to Bayesian Multilevel Models Using brms: A Case Study of Gender Effects on Vowel Variability in Standard Indonesian.
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: I...
| Published in: | Journal of Speech, Language & Hearing Research Vol. 62; no. 5; pp. 1225 - 1243 |
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| Main Authors: | , , , , |
| Format: | Article |
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American Speech-Language-Hearing Association
May2019
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| Subjects: | |
| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=136684686&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 136684686 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 10924388 1SM jtl: Journal of Speech, Language & Hearing Research issn: 10924388 maglogo: N pubinfo: dt: May2019 vid: 62 iid: 5 pid: 42 pub: American Speech-Language-Hearing Association artinfo: ui: 136684686 10.1044/2018_JSLHR-S-18-0006 ppf: 1225 ppct: 18 formats: fmt: @attributes: type: P size: 1.6MB tig: atl: An Introduction to Bayesian Multilevel Models Using brms: A Case Study of Gender Effects on Vowel Variability in Standard Indonesian. aug: au: Nalborczyk, Ladislas Batailler, Cédric Loevenbruck, Hélène Vilain, Anne Bürkner, Paul-Christian affil: Univ. Grenoble Alpes, CNRS, LPNC, 38000 Grenoble, France Department of Experimental Clinical and Health Psychology, Ghent University, Belgium Univ. Grenoble Alpes, Univ. Savoie Mont Blanc, LIP/PC2S, France Institut Universitaire de France, Paris Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000, Grenoble, France Department of Psychology, University of Münster, Germany Paul-Christian Bürkner is now with the Department of Computer Science, Aalto University, Espoo, Finland su: Education Speech Immunomodulators Multilevel models Bayesian analysis Vowels Indonesian language Data analysis sug: subj: Education Speech Administration of Education Programs Educational Support Services All Other Miscellaneous Schools and Instruction Immunomodulators Multilevel models Bayesian analysis Vowels Indonesian language Data analysis ab: 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/). pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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