Statistical methods for linguistic research: Foundational Ideas-Part II
- We provide an introductory review of Bayesian data analytical methods, with a focus on applications for linguistics, psychology, psycholinguistics, and cognitive science. The empirically oriented researcher will benefit from making Bayesian methods part of their statistical toolkit due to the many advantages of this framework, among them easier interpretation of results relative to research hypotheses and flexible model specification. We present an informal introduction to the foundational ideas behind Bayesian data analysis, using, as an example, a linear mixed models analysis of data from a typical psycholinguistics experiment. We discuss hypothesis testing using the Bayes factor and model selection using cross-validation. We close with some examples illustrating the flexibility of model specification in the Bayesian framework. Suggestions for further reading are also provided.
Author details: | Bruno NicenboimORCiDGND, Shravan VasishthORCiDGND |
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DOI: | https://doi.org/10.1111/lnc3.12207 |
ISSN: | 1749-818X |
Title of parent work (English): | Language and linguistics compass |
Publisher: | Wiley-Blackwell |
Place of publishing: | Hoboken |
Publication type: | Article |
Language: | English |
Year of first publication: | 2016 |
Publication year: | 2016 |
Release date: | 2020/03/22 |
Volume: | 10 |
Number of pages: | 23 |
First page: | 591 |
Last Page: | 613 |
Peer review: | Referiert |
Institution name at the time of the publication: | Humanwissenschaftliche Fakultät / Exzellenzbereich Kognitionswissenschaften |