MaskedPriming {DAAGxtras} | R Documentation |
Words (words
), preceded by an invisible identical or unrelated
“prime”, or non-words, were flashed in front of subjects (id
).
The time taken by the subject to identify the letter combination
as “not word” or “word” was then measured.
data(MaskedPriming)
A data frame with 6381 correct responses to words on the following 10 variables.
subjects
1
to 72
words
1
to 192
e
1
2
3
ct
HI
HU
LI
LU
. Here, HI
= high freq, identical prime;
HU = high freq, unrelated prime; LI
= low, identical;
LU = low, unrelatedf
p
rt
srt
rt
/1000, a numeric vectorlrt
rrt
srt
,
a numeric vectorThis combines the datasets from Bodner and Masson (1997, Exp 1 and Exp 2a) and Kinoshita (2006, Exp 2).
Kliegl et al (2008)
Bodner, G.E., and Masson, M. E. J. 1997 Masked repetition priming of words and nonwords: Evidence for a nonlexical basis for priming. Journal of Memory and Language 37, 268-293.
Kinoshita, S. 2006 Additive and interactive effects of word frequency and masked repetition in the lexical decision task. Psychonomic Bulletin & Review 13, 668-673.
Kliegl, R., Masson, M. E. J. and Richter, E. M. 2008. A linear mixed-effects model analysis of masked repetition priming. Manuscript.
data(MaskedPriming) str(MaskedPriming) plot(MaskedPriming[sample(6381,100), 7:10]) ## Not run: library(lme4) cmat <- matrix(c(-1, 1, 0, -1, -1, 2), 3, 2, dimnames=list(c("BM1", "BM2", "SK"), c(".BM1-2", ".BM-SK"))) m0 <- lmer(rrt ~ p*f*e + (1 | subjects) + (0 + p | subjects) + (0 + f | subjects) + (1 | words), contrasts=list(e=cmat), data=d) m1p <- lmer(rrt ~ p*f*e + (p | subjects) + (0+f | subjects) + (1 | words), contrasts=list(e=cmat) m2 <- lmer(rrt ~ p*f*e + (p + f | subjects) + (1 | words), contrasts=list(e=cmat), data=d) anova(m0, m1p, m2) ## End(Not run)