An Overview of Mixed-Effects Statistical Models for Second Language Researchers

Autor/in	Cunnings, Ian
Titel	An Overview of Mixed-Effects Statistical Models for Second Language Researchers
Quelle	In: Second Language Research, 28 (2012) 3, S.369-382 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0267-6583
DOI	10.1177/0267658312443651
Schlagwörter	Language Research; Second Languages; Data Analysis; Researchers; Second Language Learning; Statistical Analysis; Models; Computer Software + Suchen Sie Ihr Suchwort? Sprachforschung; Second language; Zweitsprache; Auswertung; Researcher; Forscher; Zweitsprachenerwerb; Statistische Analyse; Analogiemodell
Abstract	As in any field of scientific inquiry, advancements in the field of second language acquisition (SLA) rely in part on the interpretation and generalizability of study findings using quantitative data analysis and inferential statistics. While statistical techniques such as ANOVA and t-tests are widely used in second language research, this review article provides a review of a class of newer statistical models that have not yet been widely adopted in the field, but have garnered interest in other fields of language research. The class of statistical models called mixed-effects models are introduced, and the potential benefits of these models for the second language researcher are discussed. A simple example of mixed-effects data analysis using the statistical software package R (R Development Core Team, 2011) is provided as an introduction to the use of these statistical techniques, and to exemplify how such analyses can be reported in research articles. It is concluded that mixed-effects models provide the second language researcher with a powerful tool for the analysis of a variety of types of second language acquisition data. (Contains 3 notes.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10