# [FieldTrip] second-level statistical inference

Stolk, A. a.stolk at fcdonders.ru.nl
Fri Nov 25 10:04:18 CET 2011

```Hi Sara,

If I understand correctly, you want to test intra-subject differences (between conditions) at the second level? This would require the following steps:

1) subject-level statistics, which you have done already

2) grandaverage all these, with keepindividuals=yes.

3) copy the output of the grandaverage (into a dummy variable), and replace the fields containing the subject T-values with zeros (for timelock data this may be the trial fields?)

4) again timelockstatistics, as in step 1, now with the variables following step 3. this should give you the resulting statistics of contrasting intra-subject differences vs. null at the group level.

Hope this helps,

Arjen

----- "Sara Bögels" <s.bogels at psy.gla.ac.uk> schreef:

> Van: "Sara Bögels" <s.bogels at psy.gla.ac.uk>
> Aan: fieldtrip at donders.ru.nl
> Verzonden: Donderdag 24 november 2011 15:49:17
> Onderwerp: [FieldTrip] second-level statistical inference
>
> Hi all,
>
> I have been trying to do second-level statistical inference (as
> described in one of the FAQs) on ERFs, but I am not sure whether I am
>
> doing everything correctly.
>
> In the first step I calculate the T-values for the difference between
>
> two conditions (twice), which are between items, with
> ft_timelockstatistics. I put the output of all participants in a cell
>
> (called 'stat1a' and 'stat1b'). (I tried to use
> ft_timelockgrandaverage
> to combine the subjects together but it needs a field avg).
>
> Then I use ft_timelockstatistics again but  subject level. I first
> want
> to look at the difference between the two conditions. This difference
> is
> reflected in the T-values of the first step so I create a dummy which
> is
> the same as 'stat1' but I replace all the values in the field 'stat'
> per
> participant with zeros. Then I call (with appropriate cfg
> parameters):
>
> stat2a = ft_timelockstatistics(cfg,stat1a{:},dummy{:});
> stat2b = ft_timelockstatistics(cfg,stat1b{:},dummy{:});
>
> To compare the two differences (stat1a and stat1b) and thereby look at
>
> an interaction, I call:
>
> stat2a-b = ft_timelockstatistics(cfg,stat1a{:},stat1b{:});
>
> I am uncertain whether the dummy works (or is there a way to compare
> the
> t-values to zero directly?) and whether the stat1a{:} trick works with
>
> ft_timelockstatistics.
>
>
> Sara
>
>
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```