(Generalized Linear) Mixed‐Effects Modeling: A Learner Corpus Example

Stefan Τh. Gries

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Second Language Acquisition and Learning EFL/ESL Teaching and Learning Statistical Methods and Bayesian Inference

Abstract

Abstract This methods showcase article provides a detailed overview of a mixed‐effects modeling analysis of corpus data on the use of that in object and subject complementation by native speakers of English compared to its use by German and Spanish learners of English. “We emphasize that we do not claim that our illustrations are the only way to carry out these analyses, but the strategy outlined above has yielded satisfactory results.” (Bates et al., 2018, p. 5)

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2008Analyzing Linguistic Data 1973The language-as-fixed-effect fallacy: A critique of language statistics in psychological research 2008Analyzing linguistic data : a practical introduction to statistics using R 2003Collostructions: Investigating the interaction of words and constructions 2004Extending collostructional analysis 2012Models, forests, and trees of York English: Was/were variation as a case study for statistical practice 2010Redundancy and reduction: Speakers manage syntactic information density 2006Language Acquisition as Rational Contingency Learning

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2022A large-scale longitudinal study of syntactic complexity development in EFL writing: A mixed-effects model approach 2022Applying meta-analytic structural equation modeling to second language research: An introduction 2023Introduction to the special issue on Introducing bibliometrics in applied linguistics

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