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Divergence point analyses of visual world data

  • Much work has shown that differences in the timecourse of language processing are central to comparing native (L1) and non-native (L2) speakers. However, estimating the onset of experimental effects in timecourse data presents several statistical problems including multiple comparisons and autocorrelation. We compare several approaches to tackling these problems and illustrate them using an L1-L2 visual world eye-tracking dataset. We then present a bootstrapping procedure that allows not only estimation of an effect onset, but also of a temporal confidence interval around this divergence point. We describe how divergence points can be used to demonstrate timecourse differences between speaker groups or between experimental manipulations, two important issues in evaluating L2 processing accounts. We discuss possible extensions of the bootstrapping procedure, including determining divergence points for individual speakers and correlating them with individual factors like L2 exposure and proficiency. Data and an analysis tutorial areMuch work has shown that differences in the timecourse of language processing are central to comparing native (L1) and non-native (L2) speakers. However, estimating the onset of experimental effects in timecourse data presents several statistical problems including multiple comparisons and autocorrelation. We compare several approaches to tackling these problems and illustrate them using an L1-L2 visual world eye-tracking dataset. We then present a bootstrapping procedure that allows not only estimation of an effect onset, but also of a temporal confidence interval around this divergence point. We describe how divergence points can be used to demonstrate timecourse differences between speaker groups or between experimental manipulations, two important issues in evaluating L2 processing accounts. We discuss possible extensions of the bootstrapping procedure, including determining divergence points for individual speakers and correlating them with individual factors like L2 exposure and proficiency. Data and an analysis tutorial are available at https://osf.io/exbmk/.show moreshow less

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Metadaten
Author details:Kate StoneORCiDGND, Sol LagoORCiD, Daniel SchadORCiDGND
DOI:https://doi.org/10.1017/S1366728920000607
ISSN:1366-7289
ISSN:1469-1841
Title of parent work (English):Bilingualism : language and cognition
Subtitle (English):applications to bilingual research
Publisher:Cambridge Univ. Press
Place of publishing:Cambridge
Publication type:Article
Language:English
Date of first publication:2021/11/26
Publication year:2021
Release date:2024/02/27
Tag:bilingualism; bootstrapping; divergence point analyses; non-parametric approaches; visual world eye-tracking
Volume:24
Issue:5
Article number:PII S1366728920000607
Number of pages:9
First page:833
Last Page:841
Funding institution:German Research Council, German Research Foundation (DFG) [LA 3774/1-1]
Organizational units:Humanwissenschaftliche Fakultät / Strukturbereich Kognitionswissenschaften / Department Psychologie
DDC classification:1 Philosophie und Psychologie / 15 Psychologie / 150 Psychologie
4 Sprache / 40 Sprache / 400 Sprache
Peer review:Referiert
Publishing method:Open Access / Hybrid Open-Access
License (German):License LogoCC-BY - Namensnennung 4.0 International
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