Mixed-effects modeling with crossed random effects for subjects and items
This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered...
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| Published in | Journal of memory and language Vol. 59; no. 4; pp. 390 - 412 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Elsevier Inc
01.11.2008
Elsevier Elsevier BV |
| Subjects | |
| Online Access | Get full text |
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| Abstract | This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed. |
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| AbstractList | This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed. [PUBLICATION ABSTRACT] This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed. [Copyright Elsevier Inc.] This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed. This paper provides an introduction to mixed-effects models for the analysis of repeated measurement data with subjects and items as crossed random effects. A worked-out example of how to use recent software for mixed-effects modeling is provided. Simulation studies illustrate the advantages offered by mixed-effects analyses compared to traditional analyses based on quasi-F tests, by-subjects analyses, combined by-subjects and by-items analyses, and random regression. Applications and possibilities across a range of domains of inquiry are discussed. (Contains 2 figures and 10 tables.) |
| Author | Davidson, D.J. Baayen, R.H. Bates, D.M. |
| Author_xml | – sequence: 1 givenname: R.H. surname: Baayen fullname: Baayen, R.H. email: baayen@ualberta.ca organization: University of Alberta, Edmonton, Department of Linguistics, Canada T6G 2E5 – sequence: 2 givenname: D.J. surname: Davidson fullname: Davidson, D.J. email: Doug.Davidson@fcdonders.ru.nl organization: Max Planck Institute for Psycholinguistics, P.O. Box 310, 6500 AH Nijmegen, The Netherlands – sequence: 3 givenname: D.M. surname: Bates fullname: Bates, D.M. email: bates@stat.wisc.edu organization: University of Wisconsin, Madison, Department of Statistics, WI 53706-168, USA |
| BackLink | http://eric.ed.gov/ERICWebPortal/detail?accno=EJ818422$$DView record in ERIC |
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| CODEN | JMLAE6 |
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| Title | Mixed-effects modeling with crossed random effects for subjects and items |
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