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Mixed-Effects Regression Models in Linguistics

  • Dirk Speelman
  • Kris Heylen
  • Dirk Geeraerts

Table of contents

  1. Front Matter
    Pages i-vii
  2. Dirk Speelman, Kris Heylen, Dirk Geeraerts
    Pages 1-10
  3. Geert Verbeke, Geert Molenberghs, Steffen Fieuws, Samuel Iddi
    Pages 11-28
  4. Job Schepens, Frans van der Slik, Roeland van Hout
    Pages 29-47
  5. Martijn Wieling, Esteve Valls, R. Harald Baayen, John Nerbonne
    Pages 71-97

About this book

Introduction

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.

Keywords

effects models generalized linear mixed models linguistics mixed models regression semantics

Editors and affiliations

  • Dirk Speelman
    • 1
  • Kris Heylen
    • 2
  • Dirk Geeraerts
    • 3
  1. 1.Faculty of ArtsResearch Group QLVLKU LeuvenBelgium
  2. 2.Faculty of ArtsResearch Group QLVLKU LeuvenBelgium
  3. 3.Faculty of ArtsResearch Group QLVLKU LeuvenBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-69830-4
  • Copyright Information Springer International Publishing AG, part of Springer Nature 2018
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-319-69828-1
  • Online ISBN 978-3-319-69830-4
  • Series Print ISSN 2199-0956
  • Series Online ISSN 2199-0964
  • Buy this book on publisher's site
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