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 be true for any type of group - so that alone is not very exciting).
Usually there is only one time column with time-from-baseline for example

me1 0 ...
me2 1.2 ...
me 3 1.8 ...
you1 0 ..
you2 0.9 ...
he1 0
she1 0
she2 1.1
and so on (this could be in years). There can be differently many rows per subject, depending on the number of time points. Single time point subjects, can be mixed in and will help to estimate cross subject variances, but they won't really help much with estimates of longitudinal changes. Having a full group with only a single time point does not make sense in a longitudinal design.

Best, Martin

On 05/21/2016 06:42 PM, Hanbyul Cho wrote:

Dear Martin Reuter,

Thank you for your reply.

Our patients have several time points, but controls have only 1 time points,
so when I coded the patients group =1, controls groups = 0 , 
the 2. time  and  3. time2 column were same as 5. 4.X time 6. 4.X time2 column.
and 8. 7. X time and 9. 8. X time2 were all zeros.

And then, how about this X matrix (Subjects N X 5)?

1. Intercept (all '1')
2. 4.X time (from baseline time point)
3. 4.X time2
4. age
5. extra values for covariate

is it a vallid matrix for test the effects of group X time2 ?

Thank you,

Han.

On Sat, May 21, 2016 at 3:13 PM, Martin Reuter <mreuter@nmr.mgh.harvard.edu> wrote:

Hi Han,
Try to find a local statistician to help you with your analysis.
About your matrix: rows need to be number of all time points from all subject. Time 2 should probably not be there. Also columns 7-9 need to be dropped (they are just the negative of the rows before).

Best Martin

On May 21, 2016 3:32 PM, Hanbyul Cho <hanbyul.h.cho@gmail.com> wrote:

Dear FreeSurfer Team,

I processed in MATLAB for Linear Mixed Effects Models Analysis with this X matrix:

X matrix is 'Subjects N X 11', 11 columns are as follow,

1. Intercept (all '1')

2. time (from baseline time point)

3. time2

4. Patients group = 1, Control = 0

5. 4.X time

6. 4.X time2

7. Patients group = 0, Control = 1

8. 7. X time

9. 8. X time2

10. age

11. extra values for covariate

1. 

When I process this command, 

[lhTh01,lhRe01] = lme_mass_fit_EMinit(X,[1],Y,ni,lhcortex,3,4)

The MATLAB windows print the warning alarm repeatedly.

" Warning: Matrix is close to singular or badly scaled. Results may be inaccurate."

Is this X matrix something wrong?

2.

After complete   'lme_mass_fit_EMinit' process with the warning, I tried the next command,

[lhRgs01,lhRgMeans01] = lme_mass_RgGrow(lhsphere, lhRe01, lhTh01,lhcortex,2,95);

This command took a long time to process, and it caused the whole stop MATLAB works.

Is it also because of the X matrix...?

Could you let me know the solution for the X matrix problems ?

Best Wishes,

Han

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-- 
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 

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The information in this e-mail is intended only for the person to whom it is
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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.