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mso-paper-source:0;} div.Section1 {page:Section1;} --> Hi all, Im a
psychologist moving from anova to lmer for analysis of response time (and error
data) from a reaction time experiment, and have a question about specifying the
structure of random effects in the model. Many of the examples I am reading
about involve split-plot designs where effects are nested within each other
.... This is not the case here: I am using a typical repeated measures design
where each subject does everything: 30 subjects judge the laterality of a hand
shown on a computer screen, completing 18 trials in all combinations of the
following experimental factors (Angle, 8 levels (hand shown in 8 different
orientations), Laterality, 2 levels (both right and left hands shown),
Condition, 3 levels (participant holds own hands in posture a,b or c). With
repeated measures ANOVA the Error structure is specified as follows
aov(percentErrors~angle*condition*laterality+Error(subject/(angle*condition*laterality)),data=errorData)
aov(meanRT~angle*condition*laterality+Error(subject/(angle*condition*laterality)),data=RTdata)
where response variables, percentErrors and meanRT, are the percentage of
errors (out of 18 trials) and the mean reaction time over 18 trials I need
to move to lmer as variance is not constant across Angle and error data are
bounded (0,1) so I should use the binomial family my first pass (looking at
all main effects & possible interactions) is:
lmer(cbind(numErrors,numCorrect)~angle*condition*laterality+(angle*condition*laterality|subject),family=binomial),data=errorData)
where numErrors+numCorrect = 18 for each subject &
Angle-Laterality-Condition combination
lmer(meanRT~angle*condition*laterality+(angle*condition*laterality|subject),data=RTdata)
I am unsure if this is correct? Help is welcome, thanks - Nuala
Nuala Brady
School of Psychology
University College Dublin
Belfield, D4
IRELAND
+353 (0)1 716 8247
[email protected]
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