Hi Laura,
1)
you would need to model the 3 level variable differently, as 1,2,3 will
be understood as continuous and that is not what you want. Instead you
have two columns: one column for group 2, where all instances are binary
(1 if group is 2, else 0), and one for group 3. Then the intercept and
slope will be for group 1 and these columns contain the offsets for
group 2 and 3 respectively.
About interactions, make sure you really want to model all interactions.
Some may be not very meaningful and keeping the model simple is usually
a good idea. But if you want them all, add them all.
2) Zcols: Vector with the indices of the colums of X that will be
considered as random effects. Usually the intercept is a random effect
and maybe other variables (e.g. the time, if you want to allow slopes to
be different across subjects). For just the intercept column use [ 1]
ni should be correct
3) yes, but with the design above, since you model a global intercept
and then the offset of each group (or whatever that three condition
variable is) you need to make sure you interpret things correctly. E.g.
a 1 in such a column for group 2 or three indicates that there is a
difference from the first group. This is not the group 2 effect.
4) Sorry, I don't know. Maybe someone else has a suggest.
Since you have all interactions, you should be able to specify contrast
according to your test in this model and don't need to create a new one.
Your setup is a little complicated, so it would be wise to involve a
local statistician to make sure you are interpreting things correctly.
Best, Martin
On 04/07/2016 10:57 AM, Laura Rueda Delgado wrote:
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*
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
--
Martin Reuter, PhD
Assistant Professor of Radiology, Harvard Medical School
Assistant Professor of Neurology, Harvard Medical School
A.A.Martinos Center for Biomedical Imaging
Massachusetts General Hospital
Research Affiliate, CSAIL, MIT
Phone: +1-617-724-5652
Web : http://reuter.mit.edu
_______________________________________________
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is
addressed. If you believe this e-mail was sent to you in error and the e-mail
contains patient information, please contact the Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.
