Mixed-Effects Regression Models in Linguistics (Hardcover, 1st ed. 2018)

When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed. In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addresses a number of common complications, misunderstandings, and pitfalls. Topics that are covered include the use of huge datasets, dealing with non-linear relations, issues of cross-validation, and issues of model selection and complex random structures. The volume features examples from various subfields in linguistics. The book also provides R code for a wide range of analyses.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Quantitative Methods in the Humanities and Social Sciences
Release date:	February 2018
First published:	2018
Editors:	Dirk Speelman • Kris Heylen • Dirk Geeraerts
Dimensions:	235 x 155 x 17mm (L x W x T)
Format:	Hardcover
Pages:	146
Edition:	1st ed. 2018
ISBN-13:	978-3-319-69828-1
Categories:	Books > Language & Literature > Language & linguistics > Semantics (meaning) > General Books > Language & Literature > Language & linguistics > Grammar, syntax, linguistic structure > General Books > Social sciences > Sociology, social studies > Social research & statistics > General
LSN:	3-319-69828-1
Barcode:	9783319698281

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