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Why not both? Rethinking categorical and continuous approaches to bilingualism

AIMS AND OBJECTIVES: Bilingualism is a complex construct, and it can be difficult to define and model. This paper proposes that the field of bilingualism can draw from other fields of psychology, by integrating advanced psychometric models that incorporate both categorical and continuous properties....

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Autores principales: Kremin, Lena V., Byers-Heinlein, Krista
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8637352/
https://www.ncbi.nlm.nih.gov/pubmed/34867070
http://dx.doi.org/10.1177/13670069211031986
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author Kremin, Lena V.
Byers-Heinlein, Krista
author_facet Kremin, Lena V.
Byers-Heinlein, Krista
author_sort Kremin, Lena V.
collection PubMed
description AIMS AND OBJECTIVES: Bilingualism is a complex construct, and it can be difficult to define and model. This paper proposes that the field of bilingualism can draw from other fields of psychology, by integrating advanced psychometric models that incorporate both categorical and continuous properties. These models can unify the widespread use of bilingual and monolingual groups that exist in the literature with recent proposals that bilingualism should be viewed as a continuous variable. APPROACH: In the paper, we highlight two models of potential interest: the factor mixture model and the grade-of-membership model. These models simultaneously allow for the formation of different categories of speakers and for continuous variation to exist within these categories. We discuss how these models could be implemented in bilingualism research, including how to develop these models. When using either of the two models, researchers can conduct their analyses on either the categorical or continuous information, or a combination of the two, depending on which is most appropriate to address their research question. CONCLUSIONS: The field of bilingualism research could benefit from incorporating more complex models into definitions of bilingualism. To help various subfields of bilingualism research converge on appropriate models, we encourage researchers to pre-register their model selection and planned analyses, as well as to share their data and analysis scripts. ORIGINALITY: The paper uniquely proposes the incorporation of advanced statistical psychometric methods for defining and modeling bilingualism. SIGNIFICANCE: Conceptualizing bilingualism within the context of these more flexible models will allow a wide variety of research questions to be addressed. Ultimately, this will help to advance theory and lead to a fuller and deeper understanding of bilingualism.
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spelling pubmed-86373522021-12-03 Why not both? Rethinking categorical and continuous approaches to bilingualism Kremin, Lena V. Byers-Heinlein, Krista Int J Billing Articles AIMS AND OBJECTIVES: Bilingualism is a complex construct, and it can be difficult to define and model. This paper proposes that the field of bilingualism can draw from other fields of psychology, by integrating advanced psychometric models that incorporate both categorical and continuous properties. These models can unify the widespread use of bilingual and monolingual groups that exist in the literature with recent proposals that bilingualism should be viewed as a continuous variable. APPROACH: In the paper, we highlight two models of potential interest: the factor mixture model and the grade-of-membership model. These models simultaneously allow for the formation of different categories of speakers and for continuous variation to exist within these categories. We discuss how these models could be implemented in bilingualism research, including how to develop these models. When using either of the two models, researchers can conduct their analyses on either the categorical or continuous information, or a combination of the two, depending on which is most appropriate to address their research question. CONCLUSIONS: The field of bilingualism research could benefit from incorporating more complex models into definitions of bilingualism. To help various subfields of bilingualism research converge on appropriate models, we encourage researchers to pre-register their model selection and planned analyses, as well as to share their data and analysis scripts. ORIGINALITY: The paper uniquely proposes the incorporation of advanced statistical psychometric methods for defining and modeling bilingualism. SIGNIFICANCE: Conceptualizing bilingualism within the context of these more flexible models will allow a wide variety of research questions to be addressed. Ultimately, this will help to advance theory and lead to a fuller and deeper understanding of bilingualism. SAGE Publications 2021-07-16 2021-12 /pmc/articles/PMC8637352/ /pubmed/34867070 http://dx.doi.org/10.1177/13670069211031986 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Articles
Kremin, Lena V.
Byers-Heinlein, Krista
Why not both? Rethinking categorical and continuous approaches to bilingualism
title Why not both? Rethinking categorical and continuous approaches to bilingualism
title_full Why not both? Rethinking categorical and continuous approaches to bilingualism
title_fullStr Why not both? Rethinking categorical and continuous approaches to bilingualism
title_full_unstemmed Why not both? Rethinking categorical and continuous approaches to bilingualism
title_short Why not both? Rethinking categorical and continuous approaches to bilingualism
title_sort why not both? rethinking categorical and continuous approaches to bilingualism
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8637352/
https://www.ncbi.nlm.nih.gov/pubmed/34867070
http://dx.doi.org/10.1177/13670069211031986
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