The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Mixed-effects models in psychophysiology
Abstract
The current methodological policy in Psychophysiology stipulates that repeated-measures designs be analyzed using either multivariate analysis of variance (ANOVA) or repeated-measures ANOVA with the Greenhouse-Geisser or Huynh-Feldt correction. Both techniques lead to appropriate type I error probabilities under general assumptions about the variance-covariance matrix of the data. This report introduces mixed-effects models as an alternative procedure for the analysis of repeated-measures data in Psychophysiology. Mixed-effects models have many advantages over the traditional methods: They handle missing data more effectively and are more efficient, parsimonious, and flexible. We described mixed-effects modeling and illustrated its applicability with a simple example.
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Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Random-Effects Models for Longitudinal Data
Laird, N. M., & Ware, J. H. (1982) · Biometrics · doi:10.2307/2529876 · Cited by 8,923
Huynh, H., & Feldt, L. S. (1970) · Journal of the American Statistical Association · doi:10.2307/2284340 · Cited by 945
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Norms of online expressions of emotion: Comparing Facebook, Twitter, Instagram, and WhatsApp
Waterloo, S. F., Baumgartner, S. E., Peter, J., & Valkenburg, P. M. (2018) · New Media & Society · doi:10.1177/1461444817707349 · Cited by 549
Dicks, M., Button, C., & Davids, K. (2010) · Attention, Perception, & Psychophysics · doi:10.3758/app.72.3.706 · Cited by 351
Resilience as a moderator of pain and stress
Friborg, O., Hjemdal, O., Rosenvinge, J. H., Martinussen, M., Aslaksen, P. M., & Flaten, M. A. (2006) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2005.12.007 · Cited by 277
CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms
Nuutinen, M., Virtanen, T., Vaahteranoksa, M., Vuori, T., Oittinen, P., & Hakkinen, J. (2016) · IEEE Transactions on Image Processing · doi:10.1109/tip.2016.2562513 · Cited by 227
Metadata
- Authors
- BAGIELLA, E., SLOAN, R. P., & HEITJAN, D. F.
- Venue
- Psychophysiology
- Publisher
- Wiley
- Published
- 2000-01
- Volume
- 37
- Issue
- 1
- Pages
- 13-20
- ISSN
- 0048-5772 (ISSN-L)
- OpenAlex
- W2152883895
- Cited by
- 314
- References
- 3
- FWCI
- 1.13
- Type
- journal article
- Language
- en
- Open access
- closed
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- BAGIELLA, E., SLOAN, R. P., & HEITJAN, D. F. (2000). Mixed-effects models in psychophysiology. Psychophysiology. https://doi.org/10.1017/s0048577200980648
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