[FieldTrip] second-level stats with TFR

miellet at psy.gla.ac.uk miellet at psy.gla.ac.uk
Wed Dec 7 07:52:28 CET 2011


Hello,
I've got problems doing second-level stats with TFR because of the  
data structure.
I previously did it with ERF and didn't experience any difficulty. I'm  
just comparing 2 conditions so the design is very simple. The dimord  
for ERF was rpt_chan_time so I had access to the different trials.
For ERF, I computed individual t-values between my conditions and  
across trials; then averaged the result across participants and  
compared the grand-average to zero. Do you think this strategy makes  
sense?
For TFR, the dimord is chan_freq_time (with cfg.keeptrials='yes',  
before or after ft_freqbaseline). Obviously I don't want to compute  
the individual t-values across channels, freq bands or time points but  
across trials.
Do you have any idea where I could find this information please? (I  
look in previous.....previous but couldn't find anything useful. I  
also specify keeptrials at each step of the process)
Thank you very much for your help,
Sebastien

----------------------------------------------
Dr. Sébastien Miellet, Lecturer

Department of Psychology
University of Fribourg
Faucigny 2
1700 Fribourg
Switzerland

tel: +41 26 300 7666
----------------------------------------------



Quoting Sara Bögels <s.bogels at psy.gla.ac.uk>:

> 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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>



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