Bayesian data analysis in the phonetic sciences: A tutorial introduction

Volume: 71, Pages: 147 - 161
Published: Nov 1, 2018
Abstract
This tutorial analyzes voice onset time (VOT) data from Dongbei (Northeastern) Mandarin Chinese and North American English to demonstrate how Bayesian linear mixed models can be fit using the programming language Stan via the R package brms. Through this case study, we demonstrate some of the advantages of the Bayesian framework: researchers can (i) flexibly define the underlying process that they believe to have generated the data; (ii) obtain...
Paper Details
Title
Bayesian data analysis in the phonetic sciences: A tutorial introduction
Published Date
Nov 1, 2018
Volume
71
Pages
147 - 161
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