The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
Statistical and computational models of the visual world paradigm: Growth curves and individual differences
Open accessAbstract
Time course estimates from eye tracking during spoken language processing (the “visual world paradigm”, or VWP) have enabled progress on debates regarding fine-grained details of activation and competition over time. There are, however, three gaps in current analyses of VWP data: consideration of time in a statistically rigorous manner, quantification of individual differences, and distinguishing linguistic effects from non-linguistic effects. To address these gaps, we have developed an approach combining statistical and computational modeling. The statistical approach (growth curve analysis, a technique explicitly designed to assess change over time at group and individual levels) provides a rigorous means of analyzing time course data. We introduce the method and its application to VWP data. We also demonstrate the potential for assessing whether differences in group or individual data are best explained by linguistic processing or decisional aspects of VWP tasks through comparison of growth curve analyses and computational modeling, and discuss the potential benefits for studying typical and atypical language processing.
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Cites
The TRACE model of speech perception
McClelland, J. L., & Elman, J. L. (1986) · Cognitive Psychology · doi:10.1016/0010-0285(86)90015-0 · Cited by 2,956
Integration of Visual and Linguistic Information in Spoken Language Comprehension
Tanenhaus, M. K., Spivey-Knowlton, M. J., Eberhard, K. M., & Sedivy, J. C. (1995) · Science · doi:10.1126/science.7777863 · Cited by 2,929
Pfanzagl, J., & Luce, R. D. (1962) · Econometrica · doi:10.2307/1911299 · Cited by 2,469
Incremental interpretation at verbs: restricting the domain of subsequent reference
Altmann, G. T. M., & Kamide, Y. (1999) · Cognition · doi:10.1016/s0010-0277(99)00059-1 · Cited by 1,735
Allopenna, P. D., Magnuson, J. S., & Tanenhaus, M. K. (1998) · Journal of Memory and Language · doi:10.1006/jmla.1997.2558 · Cited by 1,604
Self-citationThe control of eye fixation by the meaning of spoken language
Cooper, R. M. (1974) · Cognitive Psychology · doi:10.1016/0010-0285(74)90005-x · Cited by 779
The Interface of Language, Vision, and Action: Eye Movements and the Visual World
Henderson, J. M., & Ferreira, F. (2004) · Cited by 623
Time Course of Frequency Effects in Spoken-Word Recognition: Evidence from Eye Movements
Dahan, D., Magnuson, J. S., & Tanenhaus, M. K. (2001) · Cognitive Psychology · doi:10.1006/cogp.2001.0750 · Cited by 456
Self-citationThe role of prosodic boundaries in the resolution of lexical embedding in speech comprehension
Salverda, A. P., Dahan, D., & McQueen, J. M. (2003) · Cognition · doi:10.1016/s0010-0277(03)00139-2 · Cited by 437
Huettig, F., & Altmann, G. T. M. (2005) · Cognition · doi:10.1016/j.cognition.2004.10.003 · Cited by 418
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An Introduction to Linear Mixed-Effects Modeling in R
Brown, V. A. (2021) · Advances in Methods and Practices in Psychological Science · doi:10.1177/2515245920960351 · Cited by 576
Growth Curve Analysis and Visualization Using R
Mirman, D. (2017) · Chapman & Hall/CRC eBooks · doi:10.1201/9781315373218 · Cited by 573
Self-citationThe Oxford Handbook of Information Structure
(2016) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780199642670.001.0001 · Cited by 423
Wieling, M. (2018) · Journal of Phonetics · doi:10.1016/j.wocn.2018.03.002 · Cited by 362
Metadata
- Authors
- Mirman, D., Dixon, J. A., & Magnuson, J. S.
- Venue
- Journal of Memory and Language
- Publisher
- Elsevier BV
- Published
- 2008-11
- Volume
- 59
- Issue
- 4
- Pages
- 475-494
- ISSN
- 0749-596X (ISSN-L)
- OpenAlex
- W2009240318
- Cited by
- 531
- References
- 18
- FWCI
- 5.52
- Type
- journal article
- Language
- en
- Open access
- green
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