Hi Daniel,
Sure, why not. Group differences would be shifts/offsets of the lines for each
group, while group time interaction would be different slopes.
Best, Martin
On 1. Apr 2025, at 01:23, Bondi, Daniel wrote:
Hi FreeSurfer experts,
I am using the univariate LME pipeline (lme_fit_FS & l
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Hi FreeSurfer experts,
I am using the univariate LME pipeline (lme_fit_FS & lme_F) to conduct cortical
thickness analysis on a subset of D-K atlas ROIs between two groups. Although I
am testing longitudinal group*time differences with this pipeline,
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Hello FreeSurfer experts,
I am using a mass-univariate pipeline to assess cortical thickness changes
longitudinally at a regional level (based on the D-K atlas), and have been
following this thread:
https://secure-web.cisco.com/1gfQ9eWAEqDZ3DGmI9NL7
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Hello FreeSurfer experts,
I am currently working through the linear mixed effects pipeline to assess
longitudinal cortical thickness changes in non-contact/contact athletes and
have some questions. My design matrix is as follows:
X = [ones(size(M,1),
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Hello,
I am trying to test the LME model created by Bernal using mass-univariate data.
Although my entire dataset has about 40 participants with pre- and post-season
scans, I am trying to test the pipeline with the data from one subject. On my
Mac,
Hi Dan,
Yes, this is correct. Usually you have a design where the ROI measurement (e.g.
hippocampal volume) is your dependent variable and the independent variables
are age, sex, eTIV, group etc and of course the group time interaction etc.
Best, Martin
On 1. Jul 2024, at 15:15, Dan Levitas
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Thanks Martin,
I just want to clarify that this then is the correct workflow:
1). Import the table generated from *asegstats2table*
(asegstats2table.long.table),
and select the column pertaining to the ROIs and eTIV.
2). Add to this table any covariat
Hi Dan,
No, mris_preproc and also surf2surf are functions that work on surfaces. You
would just import the volume statistics into Matlab and fill the corresponding
columns in your matrix directly, similar to using co-variates such as eTIV.
Best, Martin
On 1. Jul 2024, at 14:03, Dan Levitas w
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Hi Martin,
I wanted to ping this thread again, to confirm that my proposed
mass-univariate workflow using the subcortical segmented ROIs is
appropriate for the LME longitudinal analysis.
Thanks again.
Dan
On Thu, Jun 27, 2024 at 5:44 AM Dan Levitas
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Hi Martin,
Thanks for your reply, it's good to know that the mass-univariate approach
is still appropriate here.
Since the aseg segmentations are volumetric, can I still use the
*mris_preproc* and *mri_surf2surf* functions? If so, would the mri_prepro
Hi Dan,
You could do either one. I would recommend the mass univariate for multiple
independent test with the same design.
Best, Martin
On 26. Jun 2024, at 17:20, Dan Levitas wrote:
I recently performed an LME longitudinal mass-univariate (surface) analysis and
am now trying to do something
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Hello,
I recently performed an LME longitudinal mass-univariate (surface) analysis
and am now trying to do something similar, but with subcortical (aseg) ROIs
instead.
I first created an aseg table with the following command:
* asegstats2table \
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Hello,
as far as I can see, the subject-specific estimates are not part of the
output for the mass-univariate (lme_FSfit) algorithm (in contrast to
the simple univariate (lme_fit_FS) algorithm, where they can be found
in stats.bihat). Not sure why that
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Dear Freesurfer experts,
I am running a mixed effect model in a long analysis (lme_FSfit) with 2 random effects (intercepts and slope) and I would like to have the estimates for each subject; would you be able to help me out with this. As long as I can
Hi Amirhossein,
For GLM there is a way to compute pair-wise difference when stacking (probably
a flag to mri_stack or preproc ) . You will end up having 1 frame per
participant.
For LME I take this off the list as it gets very detailed about your specific
setup and is not really a FreeSurfer i
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Hi Martin,
I ran longitudinal pipeline on all time points so I have one template. For
the GLM approach I first calculated pc1 for baselineVs placebo (either day1
or day2) and got the lh(rh).bl-pl.thickness-pc1.fwhm10.mgh then calculated
pc1 for bl vs dr
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Thanks Martin. I assume in GLM approach I should calculate change for
session 1 and 2 and then 3 and 4 and then run difference of difference.
We actually randomized the order so half day1 is plcebo and half drug. So I
just need to be caretabout the des
Hi Amirhossein,
So you have session 1 , placebo , session 2
Another day session 3, drug, session 4 ?
Again if this is for all subjects, easiest is to subtract session 2 from 1, and
4 from 3, to get thickness/volume differences for each condition. Then compute
the difference of the differences
External Email - Use Caution
Thanks a lot Martin for the information.
We have actually 2 sessions of placebo for each subject. How do you suggest
to do the analysis including that data?
BR
On Mon, 30 Jan 2023 at 16:30, Reuter, Martin,Ph.D.
wrote:
> Hi Amirhossein,
>
> - If you h
Hi Amirhossein,
- If you have two time points for all participants,
- and the time difference is the same for all
you can simply subtract the thickness (or volume) values per participant and
run a regular GLM. LME is a little overkill here.
In LME, you have one column of ones, and one of the ti
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Hi,
I have 2 sessions of data acquired in the same day for each participant
before and after the drug intake. I wonder how to analyse this with LME
tool. I create design matrix X in 2 columns, first all ones and second the
time differences(which are the
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Hi Victor,
this file is apparently included in the NeuroStats/lme repository on GitHub (in
the ‚geodesic‘ folder’), so getting the toolbox from there might be worth a try.
Not sure why it is not included with Freesurfer.
Best,
Kersten
Am 10.02.202
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Dear Freesurfer experts,I'm using the LME model for longitudinal study
and I'm running the part of parameter estimation but MATLAB "told me"
than the file "libgeodesic.so" is not available or does not exist. So
check in FreeSurfer' folder and it's not t
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Just following up on my email below to see if anyone is able to help?
Thanks!
Nárlon Cássio
Nárlon Cássio Boa Sorte Silva, PhD
CIHR/MSFHR Postdoctoral Research Fellow
Aging, Mobility, and Cognitive Neuroscience Lab
Djavad Mowafaghian Centre for Brain
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Dear Freesurfer Experts,
Hope this finds you well
I am following the LME tutorial running LME Univariate analysis. I was
wondering if someone would kindly check my steps below? I wanted to make sure
specially that my matrix (X) and and contrast (C) w
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Dear FreeSurfer expert
I have a lme model with 3 timelines where one timeline is baseline. I two
models y = intercept + time + group + sex + time_at_baseline and y = intercept
+time +time² + group + sex +time_at_baseline
Both time² and time is
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Hi FreeSurfer Experts,
I had a question regarding contrasts for univariate LME models.
I am interested in looking at the interaction of alcohol with change in volume
across two time-points. Included in my model are covariates Gender, ICV, and
Previ
erence contrast', which has -1 and +1 at the appropriate
columns, and zeros otherwise.
Best regards,
Kersten
> Thanks!
>
> Best regards,
> Guodong
>
> >
> >
> > ------
> >
> > Date: Tue, 5 Nov 2019 09:48:06 +000
00
> From: "Diers, Kersten /DZNE"
> Subject: Re: [Freesurfer] LME model contrast matrix (Diers, Kersten
> /DZNE)
> To: "freesurfer@nmr.mgh.harvard.edu"
> Message-ID: <1572947286.4016.34.ca...@dzne.de>
> Content-Type: text/plain; charset="utf-8&qu
> To: "freesurfer@nmr.mgh.harvard.edu" > u>
> > Message-ID:
> > Content-Type: text/plain; charset="windows-1252"
> >
> > look in sess01/bold, you should see 001 and 002. Do you?
> >
> > On 10/22/2019 9:40 AM, Renew Andrade wrote:
rying to run preproc-sess -s sess01 -fsd bold -stc up -surface
> fsaverage lhrh -mni305 -fwhm 5 -per-run
> But the outcome is ERROR: no run directories found.
>
> What could be wrong?
> If you need more information let me know!
>
> Sincerely,
> Andrade.
>
>
>
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Hi Guodong,
On Di, 2019-10-22 at 16:05 +0800, Liu Guodong wrote:
> External Email - Use Caution
>
> Hello FreeSurfer Developers,
>
> I'm doing the LME tutorial, and I have some questions .
>
> 1. Why don’t we need to put the healthy
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Hello FreeSurfer Developers,
I'm doing the LME tutorial, and I have some questions .
1. Why don’t we need to put the healthy controls in the designed matrix X?
2. What’s the interpretation of the first row of the contrast matrix [1 0 0 0
0], does it
/www.neura.edu.au/help-research/subscribe>
From: "Bronwyn Overs"
To: "Freesurfer support list"
Sent: Tuesday, July 16, 2019 11:27:48 AM
Subject: Fwd: Question about Freesurfer LME analysis
Dear Freesurfer Mailing list,
I
working.
Best regards,
Kersten
From: freesurfer-boun...@nmr.mgh.harvard.edu
on behalf of Bronwyn Overs
Sent: Monday, July 22, 2019 2:45 AM
To: Freesurfer support list
Subject: [Freesurfer] Resending question about Freesurfer LME analysis
External
External Email - Use Caution
Dear FreeSurfers,
I was reading the wiki documents about how to run LME analyses in
FreeSurfer.
I found that one of the disadvantages is that, at the moment, it only
allows FDR corrections to be applied for multiple comparisons.
I have 2 patient group
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Hi Getaneh,
please find my responses inline.
On Di, 2019-01-29 at 14:18 -0600, Getaneh Bayu wrote:
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Dear Freesurfer Experts,
I have a question about how to interpret cortical thickness difference between
External Email - Use Caution
Dear Freesurfer Experts,
I have a question about how to interpret cortical thickness difference
between groups using LME MATLAB tools.
I have three groups(g0, g1, and g2) and five time points(t= 0,0.5, 1,2,3).
I am trying to use LME
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Dear Freesurfer Experts,
I have a question about how to interpret cortical thickness difference between
groups using LME MATLAB tools.
I have three groups(g0, g1, and g2) and five time points(t= 0,0.5, 1,2,3).
I am trying to use LM
External Email - Use Caution
Dear Freesurfer Experts,
I have a question about how to interpret cortical thickness difference
between groups using LME MATLAB tools.
I have three groups(g0, g1, and g2) and five time points(t= 0,0.5, 1,2,3).
I am trying to use LME
I am sorry for the inconvenience .
with regards
Getaneh
From: freesurfer-boun...@nmr.mgh.harvard.edu on behalf of Diers, Kersten /DZNE
Sent: Thursday, January 11, 2018 3:50 AM
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] LME
Hi,
I am not
External Email - Use Caution
Dear Freesurfer Experts,
I have a question about how to interpret cortical thickness difference between
groups using LME MATLAB tools.
I have three groups(g0, g1, and g2) and five time points(t= 0,0.5, 1,2,3).
I am trying to use LME model wi
External Email - Use Caution
Dear Freesurfer Experts,
I have a question about how to interpret cortical thickness difference between
groups using LME MATLAB tools.
I have three groups(g0, g1, and g2) and five time points(t= 0,0.5, 1,2,3).
I am trying to use LME model wi
/DZNE
Sent: Friday, January 12, 2018 9:50 AM
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] LME
Hi Getaneh,
thanks for the additional information.
I suspect that one source of confusion was that we have to distinguish
the univariate and the mass-univariate processing stream in the
Hi Xiaoyu,
again (see also other email) you should not run left hemispheres on the
right. This could introduce a processing bias, especially when you
force all left to be healthy and right to be diseased (or vice-versa).
Instead run your images normally and then for the univariate , simply
comp
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Hello Freesurfer Developers,
I'm attempting to use Univariate LME analysis to compare the symptomatic and
asymptomatic hemispheres of early stage Parkinson's disease patients.
I re-organized the data so that the symptomatic hemisphere is the left
he
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Hi Donatas,
please find my thoughts in-line.
Best regards,
Kersten
On So, 2018-05-27 at 11:59 +0200, Donatas Sederevicius wrote:
> External Email - Use Caution
>
> Dear Freesurfer experts,
>
> I have some doubts while running LME analysis
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Dear Freesurfer experts,
I have some doubts while running LME analysis on longitudinal data. The main
goal is to check whether longitudinal BMI scores have any impact on the
longitudinal cortical thickness changes. The model I’m thinking of is as
fo
Hello,
this is a little bit hard to tell from the outside. So for the moment I have
only some general ideas:
Did the algorithm converge in both cases? If not, I would have less confidence
in the results.
One thing to consider besides the effect size and direction is the variability
of the est
Dear Kersten,
Thanks for reply. I have new question.
When I set model use total_i_vol_stats = lme_fit_FS(X,[1 2],Y(:,2),ni)
and total_i_vol_stats = lme_fit_FS(X,[1],Y(:,2),ni).
But Bhat of two models' year have a lot different, for example, with 2 is
1.2422 without 2 is -0.5737. The direction has
Hi
sorry for the delayed response, I was not able to reply during the last
week.
You are right that the F-test provided in the LME toolbox initially
does not provide information about the direction of the effects.
You could do the following:
First, it is always useful to plot the data to get a
Dear Kersten,
I have a question about LME model. After I acquired p value, could I know
which group is bigger?
Thanks,
Lanbo
On Fri, Mar 16, 2018 at 12:13 AM, lanbo Wang wrote:
> Dear Kersten,
>
> Thanks a lot, it's really help. I have another question, after I got
> results that two group hav
Dear Kersten,
Thanks a lot, it's really help. I have another question, after I got
results that two group have significant, then how could I get direction?
Thanks,
Lanbo
On Tue, Mar 13, 2018 at 5:40 PM, Diers, Kersten /DZNE wrote:
> Hello,
>
> On Di, 2018-03-13 at 21:48 +0100, lanbo Wang wrote
Hello,
On Di, 2018-03-13 at 21:48 +0100, lanbo Wang wrote:
> Dear Kersten,
>
> Thanks, I find it. And I have other questions:
> 1. The intercepts all set as one, so in this model it doesn't
> separate different subjects, or can say no individual subject change
> rate?
If I understood correctly,
Dear Kersten,
Thanks, I find it. And I have other questions:
1. The intercepts all set as one, so in this model it doesn't separate
different subjects, or can say no individual subject change rate?
2. Should we set age according to different timepoint, or just use baseline
age?
Thanks,
Lanbo
On
Hello Lanbo,
the univariate example data can actually be downloaded from the LME
tutorial website:
Search for: "An optional sample dataset which can be used to become
familiar with the LME Matlab tools can be found here". The linked
tar.gz archive contains two folders, one for the univariate and
Dear Experts,
Hi,
There is no example detail on website of LME tutorial. I have some question
about it.
Could you send me the table of ADNI univariate example data?
Thanks,
Lanbo
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: [Freesurfer] LME
Hi Getaneh,
thanks for the additional information.
I suspect that one source of confusion was that we have to distinguish the
univariate and the mass-univariate processing stream in the LME toolbox.
The univariate stream is about a single measure like left or right or bilateral
that has already been conducted.
Best regards,
Kersten
-Original Message-
From: "Tefera, Getaneh B"
Reply-to: Freesurfer support list
To: freesurfer@nmr.mgh.harvard.edu
Cc: "Tefera, Getaneh B"
Subject: Re: [Freesurfer] LME
Date: Thu, 11 Jan 2018 21:09:21 +01
t and right cortical thickness data?
I am sorry for the inconvenience .
with regards
Getaneh
From: freesurfer-boun...@nmr.mgh.harvard.edu on behalf of Diers, Kersten /DZNE
Sent: Thursday, January 11, 2018 3:50 AM
To: freesurfer@nmr.mgh.harvard.edu
Subject:
-to: Freesurfer support list
To: Freesurfer support list
Subject: Re: [Freesurfer] LME
Date: Wed, 10 Jan 2018 17:58:58 +0100
Dear Kersten,
Thank you so much.
When I run the procedure with left and right cortical thickness data
I get different phisqhat values
Phisqhat:0.2530 for the left and
: [Freesurfer] LME
Hi Getaneh,
the estimates for D and phisq for a given analysis are contained within the
data structure that is returned by the lme_fit_FS procedure.
I.e. for the tutorial data, the command was:
total_hipp_vol_stats = lme_fit_FS(X,[1 2],Y(:,1)+Y(:,2),ni);
Dhat and phisqhat are fields
To: Freesurfer support list
Subject: Re: [Freesurfer] LME
Date: Tue, 9 Jan 2018 23:02:08 +0100
Hi Kersten.
Thank you very much .
I am not planning a new design for sample size calculation.
Can you please help me how to find those values?
Thank you
Getaneh
__
: Tuesday, January 9, 2018 5:56 AM
To: freesurfer@nmr.mgh.harvard.edu
Subject: Re: [Freesurfer] LME
Hi Getaneh,
please find my responses below.
-Original Message-
From: "Tefera, Getaneh B"
Reply-to: Freesurfer support list
To: freesurfer@nmr.mgh.harvard.edu
Subject: [Frees
Hi Getaneh,
please find my responses below.
-Original Message-
From: "Tefera, Getaneh B"
Reply-to: Freesurfer support list
To: freesurfer@nmr.mgh.harvard.edu
Subject: [Freesurfer] LME
Date: Mon, 8 Jan 2018 22:54:49 +0100
Dear Freesurfer experts,
I have three groups g0,
Dear Freesurfer experts,
I have three groups g0, g1, and g2.
I am trying to use LME model with random effects y-int and time from the base
line.
Based on the LME tutorial and the questions and answers from Freesurfer
support list:
Y=B1+B2*t+B3*g1+B4*g1*t+B5*g2+B6*g2*t+ ...
The slope of g
Dear Freesurfer experts,
I have three groups g0, g1, and g2.
I am trying to use LME model with random effects y-int and time from the base
line.
Based on the LME tutorial and the questions and answers from Freesurfer
support list:
Y=B1+B2*t+B3*g1+B4*g1*t+B5*g2+B6*g2*t+ ...
The slope of g
...@nmr.mgh.harvard.edu] On Behalf Of Donatas Sederevicius
[donatas.sederevic...@psykologi.uio.no]
Sent: Thursday, September 07, 2017 12:19 PM
To: freesurfer@nmr.mgh.harvard.edu
Subject: [Freesurfer] LME model and contrast
Dear freesurfer team,
I’m trying to use freesurfer LME tools to check whether
Dear freesurfer team,
I’m trying to use freesurfer LME tools to check whether baseline BMI scores
(BMI scores at the first timepoint) have a statistically significant
effect/impact on longitudinal thickness changes accounting for baseline age and
gender. The model I’m thinking of is:
Y_ij
Dear Martin,
Thank you so much for all the help that you had given me.
Kind regards,
Livia
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The information in this e-mail is in
Hi Livia,
I cannot help you, as I don’t know about the cluster analysis etc, maybe
someone else does.
Here some quick answers as far as what I know:
1. when running the test with
F_lhstats = lme_mass_F(lhstats,CM);
you get a structure F_lhstats which should also contain the F .
Also take a l
Dear Martin,
Thank you very much again for your reply. I did better with your help, but
I am really sorry that I still have some questions.
1. I found there are positive and negative regions in the result “sig.mgh”
map. I wonder “lme_mass_F” is a kind of F analysis or T analysis in fact.
How to
Hi Livia,
[1] only the intercept is used as random effect in the model
[1 2 ] both intercept and time (slopes) are used as random effect in the
model. Here many more parameters get estimated so you need to have
sufficient data. Often the more simple approach is better (but that can
be tested
Dear Martin,
Thank you very much for your quick reply.
I use voxel-wise mixed model analysis, and I see different design:
lhstats = lme_mass_fit_vw(X,[1],Y,ni,lhcortex);Summary: Algorithm
did not converge at 0 percent of the total number of locations.
lhstats = lme_mass_fit_vw(X,[1 2],Y,ni,
Hi Livia,
yes, 0 0 0 1 is the interaction (if longitudinal slopes = atrophy rates, differ
across groups).
When interpreting these, it makes sense to look at your model:
Y_ij = b0 + b1 t_ij + b2 g_i + b3 t_ij g_i
where t is time, g is group.
For group=0 you have
Y_ij = b0 + b1 t_ij
so b0 is th
Hi Livia,
groups should be 0 and 1, e.g. 0 for controls, 1 for disease.
Order of groups does not matter (as long as both X and Y are ordered that way).
You can do FDR or FDR2 on your final sig values. It is best to combine results
from left and right hemisphere and do a single FDR2 correction
Dear FS experts,
I want to add some in my early mail.
If the contrast CM.C= [0 0 0 1] is designed for the interaction effect(time
and group).
How to design contrasts to do the main effect about the time and group?
CM.C=[0 1 0 1] and CM.C=[0 0 1 1]? Or other?
I wonder I may be wrong in designing mat
Dear FS experts,
I are analysing longitudinal data - the difference between 2 groups (1
and 2) with 2 time points for each group (0, 1 --all the same time
interval: a month).
I followed http://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels
and with Jorge's early reply in
http://www.
Hi Matthieu,
Y = b0 + b1 tij + b2 si + b3 si * tij
(Y thickness, b0 intercept, b1 slope, b2 score, b3 score effect on
slope, where t_ij is the time of subject i at time point j, s_i is
subject score)
= (b0 + b2 si) + (b1 + b3 si) tij
so the slope is made up of (b1 + b3 si), a global comp
Hi Martin,
Thank you this helps !
Please find last question below inline.
Best,
Matthieu
Le 18 mai 2017 10:33 AM, "Martin Reuter" a
écrit :
Hi Matthieu,
1) you would put a column of score and a column of score X time. The first
allows you to test if the intercept changes based on scores (e
Hi Matthieu,
1) you would put a column of score and a column of score X time. The
first allows you to test if the intercept changes based on scores (e.g.
if hippocampal volume is affected by the score, controlling for whatever
else you included, e.g. age and gender etc) and the second interac
Hi Martin,
I will read up on interpretation of time varying covariates.
If initially I use score as variable fixed across time, and define a
variable for 'score x time' interaction:
1) Would putting only 1 to 'score x time' column (for contrast) test for
progression of correlation patterns betwee
Hi Matthieu,
replacing time by score is very different from adding score as a
covariate. Often scores are crude and often they are constant in
controls (always full score), and only vary slightly in diseased. In
those cases it may not be good to use score as a time variable.
I would either a
Hi Martin,
Thank you for this detailed answer.
Are replacing time by score or include score as time-varying covariate
leading to the same result because of looking at the same effect ?
My willing would be to find patterns of atrophy rate/progression correlated
with cognitive score. In context of
Hi Matthieu,
one option is to replace time with score in the model. That should be
straight forward.
The other option is to include score as a time-varying covariate. If
your score is not varying much across time and you are more interested
if the average score (or baseline score) affects at
Hi Martin,
Thank you. How should this variable be coded ? Should it be as age
covariate where age at baseline is used along all time points of each
subject ?
Could you provide me an example of design matrix, I don't manage to see
what does it look like to.
Best regards,
Matthieu
Le 14 mai 2017
Hi Matthieu,
yes, that is possible. Instead of group, you use a variable for your score (and
interaction etc). Sometimes it may also makes sense to use score instead of
time.
Best, Martin
> On 12 May 2017, at 10:51, Matthieu Vanhoutte
> wrote:
>
> Dear Freesurfer's experts,
>
> I have s
Dear Freesurfer's experts,
I have searched through the mailing list but haven't found any answer to my
question.
Is it possible with LME model to make correlations between for example
cortical thickness surface data and cognition scores along time ? As it is
possible to test for interaction of gr
Hi Mailing List,
I am fitting an LME model with random effects for B0 and B2, so I am using the
following to fit a spatiotemporal model:
lhstats = lme_mass_fit_Rgw(X,[1 3],Y,ni,lhTh0,lhRgs,lhsphere);
However, prior to this when i am computing the initial temporal covariance
estimates, do the s
Hi Bronwyn,
to shorten equations, lets set t = years_form_baseline
a = age
g = group
s = sex
so your model is
Y_ij = b0 + b1 t_ij + b2 a_i + b3 g_i + b4 s_i + b5 t_ij a_i + b6 t_ij g_i + b7
a_i g_i + b8 t_ij a_i g_i
(as a fist step, I would consider simplifying it, by dropping the age
interact
Hi Martin,
Thank you for your response, that is much clearer.
I am also a little confused about how to specify the exact contrasts we wish to
test and was hoping to get some advice. My design matrix X includes the
following columns:
1. Intercept
2. Years from baseline
3. Age at baseline
4. Gro
Hi Bronwyn,
I think years-between-scans should be years-from-baseline-scans . You may need
to compute that if what you have is really years between neighbouring scans.
1. Usually people use intercept and maybe years-from-baseline as random
effects. I would not include too many random effects,
Dear mailing list,
I am trying to run a LME model using the matlab tools, but I’m unsure how to
specify the model we wish to run. We have a qdec file that contains the
following columns:
fsid, fsid-abse, years between scans, age at baseline, gender, group
We want to specify a model where we can
Yes, it was arbitrary. A linear trajectory was a sufficiently good model for
the mean response over time for most of the cortex points in my analyses. Also
if you only have at most three time points per user then you can only have at
most two random effects in your mixed-model (intercept and tim
Hi Jordi
You have implicitlyincluded the reference group in your statistical model by
includingan intercept term and a time variable:
group0 intercept: ß1group0 time: ß2group1 intercept:ß1+ß3group1 time:
ß2+ß4group2 intercept:ß1+ß5group2 time: ß2+ß6
>From here you canquickly see that your prop
Dear FreeSurfer experts,
I would appreciate a confirmation regarding correctness of my approach.
I am trying to run an LME model for three groups (group1=controls, group2 and
group3) and two time points.
I followed the tutorial on
https://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsM
Dear FreeSurfer Experts,
I'm following the LME tutorial to analyze my data. The example that is given in
the tutorial is for a left hemispheric cortical thickness analysis. I would
also like to look at surface area. Would I follow the same steps? At the point
in the tutorial that uses the lme_m
Dear FreeSurfer experts,
I am following the mass-univariate (spatiotemporal) model in the LME tutorial.
My design matrix X has the following columns:
intercept, time, time², group1, group1*time, group1*time², group2, group2*time,
group2*time², sex, age, mean_thickness
I actually have 3 groups b
Dear Martin Reuter,
Thank you for your clear explanation.
Best wishes,
Han.
On Tue, May 24, 2016 at 12:41 PM, Martin Reuter wrote:
> Dear Han,
>
> if controls have only 1 time point, you cannot compare/analyse any
> measurement of change across the groups (such as atrophy rates). You can
> on
Dear Han,
if controls have only 1 time point, you cannot compare/analyse any
measurement of change across the groups (such as atrophy rates). You can
only do a cross sectional analysis at baseline.
For patients you could separately look at atrophy rates (if they differ
from zero, which should
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