Description Usage Format Details Source See Also Examples
The model call is: lmer(formula = Amplitude ~ FreqBc * LengthBc * WMCc + (1 | Subject) + (1 | Item) + (0 + WMCc | Item), data = dat)
(see details for more).
The plotting data was generated from this model with function plotLMER3d.fnc
.
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The format is: num [1:30, 1:10] -1.83 -1.95 -2.07 -2.19 -2.32 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:30] "-2.88262910798122" "-2.50331876315363" "-2.12400841832605" "-1.74469807349846" ... ..$ : chr [1:10] "-0.1857142855" "-0.1410714285" "-0.0517857144999999" "-0.0428571424999999" ...
The model includes a three-way interaction between WMCc (mean-centered working memory capacity), FreqBc (the frequency of use of the second word of a four-word sequence), and LengthBc (the length in number of letters of the second work of a four-word sequence) in addition to by-subject and by-item random intercepts and by-item random slopes for WMCc.
The data is from:
Tremblay, Antoine. (2009). Processing Advantages of Lexical Bundles: Evidence from Self-paced Reading, Word and Sentence Recall, and Free Recall with Event-related Brain Potential Recordings. Ph.D. Dissertation. University of Alberta, Edmonton, Canada. Available for download at http://www.ualberta.ca/~antoinet/ThesisDraft_10_B.pdf.
The model is from:
Tremblay, Antoine, and Newman, Aaron J. (In Preparation). The Analysis of Event-related Potentials using Linear Mixed-effects Models with Complex Random-effect Structures.
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