splitplot {languageR} | R Documentation |
Simulated lexical decision latencies with priming as treatment and reaction time in lexical decision as dependent variable.
data(splitplot)
A data frame with 800 observations on the following 11 variables.
items
w1
, w2
,
..., w40
, coding 40 word items.ritems
list
listA
and listB
.
The priming effect is counterbalanced for subjects across these
two lists, compare table(splitplot$list, splitplot$subjects)
.rlist
priming
primed
and
unprimed
.fpriming
subjects
s1
, s2
,
... s20
coding 20 subjects.rsubject
error
int
RT
R. H. Baayen, D. J. Davidson and D. M. Bates. Mixed-effects modeling with crossed random effects for subjects and items. Manuscript under revision for Journal of Memory and Language.
## Not run: data(splitplot) table(splitplot$list, splitplot$subjects) library(lme4) dat.lmer1 = lmer2(RT ~ list*priming+(1+priming|subjects)+(1+list|items),data=dat) dat.lmer2 = lmer2(RT ~ list*priming+(1+priming|subjects)+(1|items),data=dat) dat.lmer3 = lmer2(RT ~ list*priming+(1|subjects)+(1|items),data=dat) dat.lmer4 = lmer2(RT ~ list*priming+(1|subjects),data=dat) anova(dat.lmer1, dat.lmer2, dat.lmer3, dat.lmer4) print(dat.lmer3, corr=FALSE) ## End(Not run)