Hi all,
I have collected response time data from 178 participants ('sub') for
each combination of 4 within-Ss factors ('con','int','tone','cue').
Additionally, I have recorded the gender of each participant, so this
forms a between-Ss factor ('gender'). Normally this would be analyzed
using aov:
a=read.table('http://tinyurl.com/4pv5mh')
a$sub = factor(a$sub)
aov( #this may take a while!
x~gender*con*int*tone*cue+Error(sub/(con*int*tone*cue))
,data=a
)
However, I'd like to also look at any effects of age, recorded in
months ('age'). Since subjects were randomly sampled, their age should
be a random effect and it is furthermore an unbalanced factor (N
varies across levels of age). So I'm seeking the proper formulas to
use in lme(). The following attempt yields the following error:
library('nlme')
lme(
x ~ gender*con*int*tone*cue
, random = ~ 1 | sub*age
, data = a
)
Error in getGroups.data.frame(dataMix, groups) :
Invalid formula for groups
I would be very grateful for any suggestions.
Cheers,
Mike
--
Mike Lawrence
Graduate Student, Department of Psychology, Dalhousie University
Website: http://memetic.ca
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