[FieldTrip] second-level statistical inference

[Eric Maris]

Hi Sara,


I'm replying to your initial question (somewhere below in this email).

Why don't you calculate per-subject averages in the two within-subject 
experimental conditions (using timelockgrandaverage with 
keepindividual='yes'), and then do your second-level inference on these 
averages? See also the Fieldtrip statistics tutorials.

Best,

Eric Maris


> -----Original Message-----
> From: Sara Bögels [mailto:s.bogels at psy.gla.ac.uk]
> Sent: vrijdag 25 november 2011 12:52
> To: fieldtrip at donders.ru.nl
> Subject: Re: [FieldTrip] second-level statistical inference
>
> Hi Arjen,
>
> Thank you very much for your answer. That sounds good, but step 2 does
> not work straightforwardly, since matlab gives the error message that it
> cannot find an avg field (which would not be in the structure created by
> ft_timelockstatistics). Just saying cfg.parameter = 'stat' does not
> work. I tried to get around that by inserting an avg field which is the
> same as the stat field for each participant. Matlab also asked for an
> fsample field, which I inserted from an earlier datafile. Then it
> worked. Is it ok to do this?
>
> I did step 3 as well, using the field individual (which you get by
> keepindividuals = 'yes'). In step 4, I should just use cfg.statistic =
> 'depsamplesT', right (because the variables are within subject)?
>
> Thank you!
> Sara
>
> On 25/11/2011 09:04, Stolk, A. wrote:
> > 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.
> >>
> >> Thanks in advance for your answer.
> >>
> >> Sara
> >>
> >>
> >> _______________________________________________
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