Description Usage Format References Examples
Auditory lexical decision latencies for Danish complex words.
1 |
A data frame with 3326 observations on the following 16 variables.
Subject
a random-effect factor coding participants in the experiment.
Word
a random-effect factor coding the words for which auditory lexical decision responses were elicited.
Affix
a random-effect factor coding the affixes in the words.
LogRT
the dependent variable, log response latency.
PC1
first principal component orthogonalizing the four response latencies preceding the current trial in the experiment.
PC2
second principal component orthogonalizing the four response latencies preceding the current trial in the experiment.
PrevError
factor with levels CORRECT
and ERROR
coding whether the preceding trial elicited a correct lexical decision.
Rank
the trial number in the experiment.
Sex
factor coding the sex of the participant,
with levels F
(female) and M
(male).
LogWordFreq
log-transformed word frequency.
LogAffixFreq
log-transformed affix frequency.
ResidFamSize
residualized morphological family size (taking out LogWordFreq
and LogAffixFreq
).
ResidSemRating
residualized semantic rating (taking out morphological family size).
LogCUP
log-transformed complex uniqueness point (CUP).
LogUP
log-transformed uniqueness point (UP).
LogCUPtoEnd
log of the distance (in msec) from the CUP to the end of the word.
L. Balling and R. H. Baayen (2008). Morphological effects in auditory word recognition: Evidence from Danish. Submitted to Language and Cognitive Processes.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## Not run:
data(danish)
require(lme4)
require(lmerTest)
require(optimx)
# ---- mixed-effects regression with three random intercepts
danish.lmer = lmer(LogRT ~ PC1 + PC2 + PrevError + Rank +
ResidSemRating + ResidFamSize + LogWordFreq*LogAffixFreq*Sex +
poly(LogCUP, 2, raw=TRUE) + LogUP + LogCUPtoEnd +
(1|Subject) + (1|Word) + (1|Affix), data = danish,
control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")))
danish.lmerA = lmer(LogRT ~ PC1 + PC2 + PrevError + Rank +
ResidSemRating + ResidFamSize + LogWordFreq*LogAffixFreq*Sex +
poly(LogCUP, 2, raw=TRUE) + LogUP + LogCUPtoEnd +
(1|Subject) + (1|Word) + (1|Affix), data = danish,
control=lmerControl(optimizer="optimx",optCtrl=list(method="nlminb")),
subset=abs(scale(resid(danish.lmer)))<2.5)
summary(danish.lmerA)
## End(Not run)
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