[R-sig-ME] ERPs lme covariates

Phillip Alday phillip.alday at mpi.nl
Wed Aug 9 17:14:30 CEST 2017

Yes, this is one of the advantages of using mixed-effects models
compared to classical rmANOVA. But there are all sorts of subtle issues
with controlling co-variates:

(and make sure to read the Westfall and Yarkoni paper linked there)


although I do recommend including these covariates in general and
especially in psycholinguistic studies: https://arxiv.org/abs/1602.04565

Note, however, that lme is in the nlme package, while lmer is the
corresponding function from lme4. See
https://stats.stackexchange.com/q/5344/26743 for a comparison.


On 05/12/2017 04:05 PM, Alexandre Obert wrote:
> Dear all,
> I'm working on ERPs data from a language comprehension study and I'm
> confronting to some problems with items' features.
> Briefly, participants saw words on a screen and have to decide if
> they're meaningful or not.
> Some of them were meaningful (condition 1), others not (condition 2) and
> others were ambiguous (condition 3).
> Using classical ANOVA, I observed significant differences.
> However, words came with characteristics such as frequency, number of
> letters and so on...that I would like to control for.
> In other words, I would like to test the effect of the condition and
> control the words' features in a same analysis.
> I think that lme from lme4() could compute such analysis, is-this right?
> Regards,

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