Hi Martin,
Thank you that makes sense now.
I don't seem to be able to read a file into matlab containing hippocampal
subfield volumes instead of the standard aseg using fast_ldtable. I haven't
changed anything other than substituting hippocampal volume for dentate gyrus
volumes. So the file consists of columns fsid, fsid-base, weeks, group,
left_GC-ML-DG, right_GC-ML-DG, EstimatedICV. 276 rows.
The error I am getting in matlab is:
'Subscripted assignment dimension mismatch.
Error in fast_ldtable (line 84)
tbl(nthrow-1,nthcol-1) = sscanf(char(s(nth)),'%f'); '
Do you have any idea what the problem is?
Thanks,
Amanda
________________________________
From: freesurfer-boun...@nmr.mgh.harvard.edu
<freesurfer-boun...@nmr.mgh.harvard.edu> on behalf of Martin Reuter
<mreu...@nmr.mgh.harvard.edu>
Sent: 03 August 2017 08:15:29
To: Freesurfer support list
Subject: Re: [Freesurfer] Univariate Linear Mixed Effects
Hi Amanda,
the C matrix below has 14 columns ( 3 + 5 + 6 ).
To find out what hypothesis are tested, look at the corresponding columns.
column 4 for example is the MCIs slope delta with respect to controls (so slope
difference MCIs and CN)
the next test is slope difference between MCIs and MCIc
and finally slope difference between MCIc and AD.
Your test 0 0 0 1 similarly tests slope difference between your two groups. And
yes, the remaining columns would be control variables .
Best, Martin
On 31. Jul 2017, at 13:38, Worker, Amanda
<amanda.wor...@kcl.ac.uk<mailto:amanda.wor...@kcl.ac.uk>> wrote:
Hi there,
I am currently working through the linear mixed effects example for hippocampal
volume on the wiki and I can't quite get my head around how the contrast matrix
is set up.
In the example, the design matrix has 14 columns but the contrast matrix only
seems to have 5 (below), could you explain why that is please? And also what
hypotheses these three different contrasts are testing?
C = [zeros(3,3) [1 0 0 0 0; -1 0 1 0 0; 0 0 -1 0 1] zeros(3,6)];
At the moment I have a simple design with two groups, 4-5 time points so I have
a design matrix with 4 columns (intercept, weeks, group, group*time) and the
contrast I am using is [0 0 0 1] to test the interaction term. If I were to add
covariates such as age and gender would I simply add two more columns to my
design matrix and contrast to look like this...[0 0 0 1 0 0]?
Thanks in advance for your help.
Amanda
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