languageR (version 1.5.0)

danish: Danish auditory lexical decision

Description

Auditory lexical decision latencies for Danish complex words.

Usage

data(danish)

Format

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.

References

L. Balling and R. H. Baayen (2008). Morphological effects in auditory word recognition: Evidence from Danish. Submitted to Language and Cognitive Processes.

Examples

# 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)
# }