[R-sig-ME] random effects - multiple sessions

ji@verissimo m@iii@g oii gm@ii@com ji@verissimo m@iii@g oii gm@ii@com
Wed Feb 9 21:28:43 CET 2022

Hi Cátia,
This depends on the contrasts of session AND prob.With treatment
contrasts for session and session 2 as the reference level (for
example), you'd get the 1vs.2 and 2vs.3 comparisons, and  you could
simply do the same kinds of sums that you already did to get all three
Alternatively,rt ~ 1 + session + prob:session + (1 + session +
prob:session | subj)would give you the prob effect in each of the three
sessions, as well as by-participant random adjustments on those.
Perhaps this is a more direct way of getting what you're after.
To bring group in.... not sure. Maybe:
1 + group * (session + prob:session)
On Wed, 2022-02-09 at 19:31 +0000, Cátia Ferreira De Oliveira via R-
sig-mixed-models wrote:
> Hello,
> I am interested in modeling a learning effect per session and
> perparticipant and then extracting the random effects per participant
> so I canuse them for correlations. How can I do that?
> If I have one contrast between 2 sessions (1 vs 2) I would do:
> model_all = lmer(rt ~ group * prob * session +
> (1+prob*session|subj),data=session, REML=FALSE)
> df_all = data.frame(coef(model_all$subj))
> df$session_1 = df$prob
> df$session_2 = df$prob + df$session + df[, "prob:session"] # add up
> themain-effects and the interaction to get the other sessionBut how
> can I extend this if I have 3 sessions and I want to contrast
> themsequentially - 1 vs 2 and then 2 vs 3?
> Thank you,
> Catia

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