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FSL  June 2009

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Subject:

Re: Error message in output from 3x2 ANOVA

From:

Steve Smith <[log in to unmask]>

Reply-To:

FSL - FMRIB's Software Library <[log in to unmask]>

Date:

Wed, 3 Jun 2009 08:46:06 +0100

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (146 lines)

Hi - sounds like you have bad outliers - I would start by looking at  
the "filtered_func_data" and "var_filtered_func_data" inputs to the  
higher-level analyses, that are stored in the ---.gfeat/cope*.feat  
directories. Load these into FSLView, turn on timeseries viewing, and  
check for clear outlier subjects.

Cheers.


On 3 Jun 2009, at 08:42, Raymond Salvador wrote:

> Dear Steve,
>
> Thanks for your quick answer. There is no contrast called "error". I  
> have checked the log files for each high level cope and, in the  
> iterations it is full of "ndtri domain error" followed by message:
>
> WARNING: The passed in varcope file, tmpvarcope00.., contains voxels  
> inside the mask with zero (or negative) values. These voxels will be  
> excluded from the analysis.
>
> The output images are with extensive yellow "activations".
>
> Thanks again
>
> Raymond Salvador
>
>
>
> 2009/6/3 Steve Smith <[log in to unmask]>
> Hi - If this message appeared at the top of your HTML report, it is  
> _possible_ that this has just been picked up because it has found  
> the word "error" in one of your contrast names - is that possible?    
> If not - then you need to look through the more detailed log page to  
> see where the problem has occurred.
>
> Cheers.
>
>
>
> On 2 Jun 2009, at 11:40, Raymond Salvador wrote:
>
> Dear FSL staff,
>
> I'm running a full factorial 3X2 ANOVA and I keep on having the same  
> message in the output:
>
> "Errors occurred during the analysis"
>
> Although the model is unbalanced, it contains several individuals in  
> each of the 3x2 = 6 levels. I think the dessign matrix is OK. I  
> started from a full matrix with redundant columns
>
> mean    P1    P2    G1    G2    G3    P1_G1    P1_G2    P1_G3     
> P2_G1    P2_G2     
> P2_G3 
>                                                                                                                          1 
>     1    0    1    0    0    1    0    0    0    0     
> 0 
>                                                                                                                                                                                             1 
>     1    0    0    1    0    0    1    0    0    0     
> 0 
>                                                                                                                                                                                             1 
>     1    0    0    0    1    0    0    1    0    0     
> 0 
>                                                                                                                                                                                             1 
>     0    1    1    0    0    0    0    0    1    0     
> 0 
>                                                                                                                                                                                             1 
>     0    1    0    1    0    0    0    0    0    1     
> 0 
>                                                                                                                                                                                             1 
>     0    1    0    0    1    0    0    0    0    0    1
>
> Where P and G are factors with 2 and 3 levels (for simplicity I only  
> show one row per combination of levels, but there are as many rows  
> as individuals).
>
> Then, I have eliminated columns to obtain a full rang matrix (with 6  
> linearly independent columns)
>
> mean    P1    G1    G2    P1_G1    P2_G3
> 1    1    1    0    1    0
> 1    1    0    1    0    0
> 1    1    0    0    0    0
> 1    0    1    0    0    0
> 1    0    0    1    0    0
> 1    0    0    0    0    1
>
> This is the design matrix I've used (but moving the mean column of  
> ones to the end). I have set a contrast for each column (EV) but the  
> last one (coding for the mean).
>
> C1    1    0    0    0    0    0
> C2    0    1    0    0    0    0
> C3    0    0    1    0    0    0
> C4    0    0    0    1    0    0
> C5    0    0    0    0    1    0
>
> And I've asked for three different F tests
>
> 1) One for C1 (main effect of factor P [with two levels])
> 2) One for C2 and C3 (main effect of factor G [with three levels])
> 3) One for C4 and C5 (columns coding for interaction)
>
> I haven't centered any column as (I understand it) centered and  
> uncentered vectors span exactly the same linear subspaces, and they  
> are equivalent in an F-test comparing the full model with a nested  
> submodel. Here I'm assuming that each required F-test is related to  
> a comparison between the full model and the submodel without the  
> columns of the contrasts included in the F-test (as it is usually  
> the case in standard GLM theory). Is that right?
>
> I've have used FLAME1 and Mixed OLS, with common variance estimate  
> for all groups (Group 1 for all), leading to the same error message.
>
> Sorry for this loooooonnngg question/explanation, and thanks very  
> much in advance.
>
>
> Raymond Salvador
>
>
>
>
>
> ---------------------------------------------------------------------------
> Stephen M. Smith, Professor of Biomedical Engineering
> Associate Director,  Oxford University FMRIB Centre
>
> FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
> +44 (0) 1865 222726  (fax 222717)
> [log in to unmask]    http://www.fmrib.ox.ac.uk/~steve
> ---------------------------------------------------------------------------
>


---------------------------------------------------------------------------
Stephen M. Smith, Professor of Biomedical Engineering
Associate Director,  Oxford University FMRIB Centre

FMRIB, JR Hospital, Headington, Oxford  OX3 9DU, UK
+44 (0) 1865 222726  (fax 222717)
[log in to unmask]    http://www.fmrib.ox.ac.uk/~steve
---------------------------------------------------------------------------

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