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Hi Matthieu,

It's difficult to tell as it depends on the degrees of freedom. However, you can use the option "-zstat" so that the output statistics will be converted to z. Then things should be in a more familiar range.

All the best,

Anderson


On 13 October 2015 at 10:47, Matthieu Vanhoutte <[log in to unmask]> wrote:
Dear Anderson,

Thank you !

If i used unthresholded t-statistic (or v-statistics) maps, what range have I to consider ? E.g., in one t-statistic map, T varies from -10 to 10 so have I to consider negative, positive or both values according to my contrast ?

Best regards,

Matthieu


2015-10-11 10:17 GMT+02:00 Anderson M. Winkler <[log in to unmask]>:
Hi Matthieu,

The -ise is needed still.

All the best,

Anderson


On 10 October 2015 at 21:09, Matthieu Vanhoutte <[log in to unmask]> wrote:

Hi Anderson,

So I will have to use the -eb and -vg options and not the -ise any more ?
Isn't -ise option needed in m'y case ?

Best regards,

Matthieu

Le 10 oct. 2015 12:26, "Anderson M. Winkler" <[log in to unmask]> a écrit :
Hi Matthieu,

Hmm, I think may have meant to make a change but didn't. Well, it won't matter in this case as the -ise is transparent to the block definitions with within-block shuffling, so try repeating but using the options "-eb VarianceGroup.csv -vg auto", that is, it will use the VG file as EB, and from these, define automatically the actual VG. This is the same as "-eb VarianceGroup.csv -vg VarianceGroup.csv".

All the best,

Anderson


On 10 October 2015 at 10:02, Matthieu Vanhoutte <[log in to unmask]> wrote:

Dear Anderson,

Many thanks for all these detailed explanations !

However I used the -vg option un my command line with variance group differences between subjects in the .csv file, but still got t-stat and not v-stat outputed of PALM...

How could it be possible ?

Best regards,

Matthieu

Le 10 oct. 2015 10:42, "Anderson M. Winkler" <[log in to unmask]> a écrit :
There are two things going on:

1) The two contrasts can go in the same .csv file, i.e., one contrast per row. This single file is supplied with -t. Or, as you did, the -d can be supplied twice, although for this case doing this seems a bit cumbersome (multiple designs can be considered, but usually when these are different). It's fine though.

2) In the t-stat (produced when -vg is omitted, or if all subjects are in the same VG), the results aren't necessarily valid, as the assumptions of the test are violated twice: first the interpretation of "there is a difference in means" only stands if the variances are the same, and second, the unrestricted permutation test requires that the variances are the same so as to preserve exchangeability. The v-stat (produced when -vg is supplied) is valid.

I'll reply the last one next.

 

I have tried to launch PALM with one sample t-test on the 4D COPEs image (merges of all subjects' COPE), with the following command line :

palm -i /SUBJECTDIR/4D_COPE.nii
-d /SUBJECTDIR/design.csv
-t /SUBJECTDIR/ContrastPos.csv
-t /SUBJECTDIR/ContrastNeg.csv
-vg /SUBJECTDIR/VarianceGroup.csv
-ise
-save1-p
-o /SUBJECTDIR/Prefix


with design.csv a unique column vector of 1 (number of subjects = 7), ContrastPos.csv = 1 and ContrastNeg.csv = -1 (because I wanna test two t-contrast)  and

VarianceGroupe.csv =[
2
3
2
4
4
3
3
];

and got this error message :

Error using palm_takeargs (line 1217)
More t-contrast files (2) than valid design files (1) were supplied.

Error in palm_core (line 32)
[opts,plm] = palm_takeargs(varargin{:});

Error in palm (line 80)
palm_core(varargin{:});

Error in PALM_LEMP (line 3)


So in order to test sequentially contrast 1 then -1, I tried (is it not possible otherway ?) :

palm -i /SUBJECTDIR/4D_COPE.nii
-d /SUBJECTDIR/design.csv
-t /SUBJECTDIR/ContrastPos.csv
-d /SUBJECTDIR/design.csv
-t /SUBJECTDIR/ContrastNeg.csv
-vg /SUBJECTDIR/VarianceGroup.csv
-ise
-save1-p
-o /SUBJECTDIR/Prefix


and got no significant results on corrected (fwep) t-stat and not vstat (as you mentioned above with the Aspin–Welch's), is it normal ?

Is my design, contrasts and command line correct to test positive or negative longitudinal effect on my 7-subjects group ?