The Bayesian Revolution in Second Language Research: An Applied Approach. Issue 4 (9th August 2018)

• Record Type: Journal Article
• Authors: Norouzian, Reza; de Miranda, Michael; Plonsky, Luke
• Is Part Of: Language learning. Volume 68:Issue 4(2018)
• Page Start: 1032
• Page End: 1075
• Publication Date: 2018-08-09
• Subjects: Bayesian methods -- frequentist methods -- effect size -- second language research -- research methods; Language and languages -- Periodicals; Language and languages -- Study and teaching -- Periodicals; Linguistics; 407
• DOI: 10.1111/lang.12310
• Languages: English
• ISSNs: 0023-8333

Abstract

Abstract : Frequentist methods have long dominated data analysis in quantitative second language (L2) research. Recently, however, several empirical fields have begun to embrace alternatives known as Bayesian methods. Using an open‐source approach, we provide an applied, nontechnical rationale for Bayesian methods in L2 research. First, we compare the conceptual underpinning of Bayesian and frequentist methods. Second, using real as well as carefully simulated examples, we introduce and apply Bayesian methods to various research designs. Third, to promote the use of Bayesian methods in L2 research, we introduce a free Web‐accessed point‐and‐click software package (https://rnorouzian.shinyapps.io/bayesian-t-tests ) as well as a suite of flexible R functions developed by the first author. Additionally, we demonstrate Bayesian methods for conducting secondary analysis on previously published literature. Finally, we discuss practical and theoretical dimensions of a Bayesian revolution in L2 research. Open Practices: This article has been awarded Open Materials and Open Data badges. All materials and data are publicly accessible via the Open Science Framework athttps://osf.io/jxd47, the IRIS Repository athttps://www.iris-database.org, and GitHub athttps://github.com/rnorouzian/i/blob/master/i.r . Learn more about the Open Practices badges from the Center for Open Science:https://osf.io/tvyxz/wiki .