A gentle introduction to Bayesian statistics, with applications to bilingualism research

Abstract Bayesian analyses have been increasingly adopted in psychology and linguistics as an addition (or replacement) to traditional frequentist methods. However, Bayesian methods are not yet widely applied in bilingualism research, possibly because existing introductions and tutorials have not been directed specifically at our field. The current paper highlights the advantages of Bayesian statistics to the bilingualism researcher, by providing both an introduction to its foundational principles and a practical tutorial on estimation and hypothesis testing using the brms R package. The examples build up from simple linear regression to more advanced mixed-effects models and showcase different aspects of a Bayesian workflow. All data, code, models, and supplementary materials are publicly available at https://osf.io/n3jgm/ .

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Publication Details

Journal
Linguistic Approaches to Bilingualism
Published
2025-05-20
DOI
https://doi.org/10.1075/lab.24027.ver
Citations
4
Primary Topic
Linguistic Variation and Morphology
Type
article
Field-Weighted Citation Impact
24.52
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article

A gentle introduction to Bayesian statistics, with applications to bilingualism research

João Veríssimo
4 citations
Linguistic Approaches to Bilingualism
Linguistic Variation and Morphology
24.52
article

A gentle introduction to Bayesian statistics, with applications to bilingualism research

João Veríssimo
article en
4 citations

Abstract

Abstract Bayesian analyses have been increasingly adopted in psychology and linguistics as an addition (or replacement) to traditional frequentist methods. However, Bayesian methods are not yet widely applied in bilingualism research, possibly because existing introductions and tutorials have not been directed specifically at our field. The current paper highlights the advantages of Bayesian statistics to the bilingualism researcher, by providing both an introduction to its foundational principles and a practical tutorial on estimation and hypothesis testing using the brms R package. The examples build up from simple linear regression to more advanced mixed-effects models and showcase different aspects of a Bayesian workflow. All data, code, models, and supplementary materials are publicly available at https://osf.io/n3jgm/ .

Linguistic Approaches to BilingualismVol. 15(4)
University of Lisbon (PT), University of Reading (GB)
Openalex Percentile: Top 1%
Linguistic Variation and Morphology
24.52
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A gentle introduction to Bayesian statistics, with applications to bilingualism research — João Veríssimo · Linguistic Approaches to Bilingualism (2025) | TGRS Research Map | TGRS