Generalizability in mixed models: Lessons from corpus linguistics

Freek Van De Velde; Stefano De Pascale; Dirk Speelman

doi:10.1017/S0140525X21000236

Generalizability in mixed models: Lessons from corpus linguistics

Freek Van De Velde, Stefano De Pascale, Dirk Speelman

Linguistics and Literary Studies

Research output: Contribution to journal › Article › peer-review

Abstract

Part of the generalizability issues that haunt controlled lab experiment designs in psychology, and more particularly in psycholinguistics, can be alleviated by adopting corpus linguistic methods. These work with natural data. This advantage comes at a cost: in corpus studies, lexemes and language users can show different kinds of skew. We discuss a number of solutions to bolster the control.

Original language	English
Article number	e34
Journal	Behavioral and Brain Sciences
Volume	45
DOIs	https://doi.org/10.1017/S0140525X21000236
Publication status	Published - 10 Feb 2022

Bibliographical note

Publisher Copyright:
© The Author(s), 2022. Published by Cambridge University Press.

Copyright:
Copyright 2022 Elsevier B.V., All rights reserved.

Access to Document

10.1017/S0140525X21000236

Link to publication in Scopus

Cite this

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