| beginningReaders | R Documentation |
Visual lexical decision latencies for beginning readers (8 year-old Dutch children).
data(beginningReaders)
A data frame with 7923 observations on the following 13 variables.
Worda factor for the words.
Subjecta factor for the subjects.
LogRTa numeric vector with the log-transformed reaction time (in ms).
Triala numeric vector coding the rank of the trial in the experimental list.
OrthLengtha numeric vector coding the word's length in letters.
LogFrequencya numeric vector with log-transformed frequency in Vermeer's frequency dictionary of Dutch children's texts.
LogFamilySizea numeric vector with the log-transformed morphological family size count (with family members judged to be unknown to young children removed).
ReadingScorea numeric vector with a score for reading proficiency.
ProportionOfErrorsa numeric vector for the proportion of error responses for the word.
PC1a numeric vector for the first principal component of a PCA orthogonalization of the preceding 4 reaction times
PC2a numeric vector for the second principal component of a PCA orthogonalization of the preceding 4 reaction times
PC3a numeric vector for the third principal component of a PCA orthogonalization of the preceding 4 reaction times
PC4a numeric vector for the fourth principal component of a PCA orthogonalization of the preceding 4 reaction times
Perdijk, K., Schreuder, R., Verhoeven, L. and Baayen, R. H. (2006) Tracing individual differences in reading skills of young children with linear mixed-effects models. Manuscript, Radboud University Nijmegen.
## Not run:
data(beginningReaders)
require(lme4)
require(optimx)
require(lmerTest)
beginningReaders.lmer = lmer(LogRT ~ PC1 + PC2 + PC3 + ReadingScore +
OrthLength + I(OrthLength^2) + LogFrequency + LogFamilySize +
(1|Word) + (1|Subject) + (0+LogFrequency|Subject) +
(0+OrthLength|Subject) + (0+PC1|Subject),
data = beginningReaders,
control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")))
summary(beginningReaders.lmer)
## End(Not run)
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