Dear FreeSurfers and LME experts,

I've just started using the LME toolbox by Bernal-Rusiel et al (2012, 2013) in 
Matlab, apart from FreeSurfer. My experimental design includes one 
between-subjects factor (group with two levels, 24 vs 22 subjects), and two 
within-subjects (WS) factors (day with two levels, and condition with three 
levels). As far as I understand, the LME toolbox can be used for longitudinal 
data and for investigating modulations of neural activity with behavioral 
measures. However, it's been difficult for me to set up both the design matrix 
and the input of the LME functions given three fixed factors in my design (I 
haven't included behavior yet). So I have a few questions that I hope you can 
help me answer. I follow these steps:

1) Following the wiki, I've created a pre-design matrix, M, with:
First column: Day factor coded as 0 (first day) and 7 (7 days later, as during 
acquisition).
Second column: Group factor binary coded.
Third column: Condition factor coded with dummy variables 1 to 3 (three 
conditions in total). I don't know if this is correct; I have failed to find in 
the mailing list any reference to an additional repeated measure besides time 
in LME models.
>From here, I've created the design matrix X adding a column of 1's for the 
>intercept, adding the pre design matrix M, and adding columns for every 
>possible interaction by multiplying element-wise the columns of M (including 
>two-way and three-way interactions).

2) I then use lme_mass_fit_vw, but I have doubts about some inputs
Zcols: column 1 in X
ni: created a vector with 6 for all subjects (in total there are 6 repeated 
measures, 2 of day and 3 of condition)
I kept the others as default.

3) lme_mass_F for statistics of fixed effects. I check main effects and 
interactions with contrasts based on the design matrix X: placing a 1 in the 
column position corresponding to each effect of interest.

4) lme_mass_FDR2 for correcting the F stats for multiple comparisons. I would 
like to compare the results using AlphaSim's Monte-Carlo simulations, however 
I'm not sure what image to use to estimate the smoothness. Would you have a 
suggestion?

Could you please let me know if this procedure is sound? Also, if I'm 
interested in specific comparisons or post-hoc tests, e.g. Group 1$Day 
1$Condition 3 vs. Group 1$Day 2$Condition 3, would I need a separate model for 
that? And lastly, for the analysis including the behavioral measures, should I 
just include them as a forth column in the pre-design matrix M and add the 
relevant effects in X?

I hope I haven't overwhelmed you with so many questions. I would greatly 
appreciate any suggestion you can provide.


Best regards,


Laura Rueda

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