[FieldTrip] Difference in trial number per condition

Pelt, S. van (Stan) stan.vanpelt at donders.ru.nl
Fri Jun 17 10:51:12 CEST 2016

Hi Zsolt,

The amount to which this may be a concern will depend on the measures you want to compare. Also, the risk of drawing incorrect (qualitative) conclusions will of course mainly be large around your statistical threshold value (e.g. p=0.05). Power differences might become biased if groups have unequal size, power begin a squared value. See for a suggested numerical correction method for this, when comparing power spectra or e.g. Bokil et al., 2007 (http://www.ncbi.nlm.nih.gov/pubmed/16945422), but I assume there are also other solutions going around.


From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Zsolt Turi
Sent: vrijdag 17 juni 2016 9:32
To: FieldTrip discussion list
Subject: [FieldTrip] Difference in trial number per condition


I was wondering if FieldTrip has an optimized solution for such situations when the amount of trials in one condition markedly differs from the number of trials in the other (e.g., the ratio is 1:3 or 1:4).

On the website I have found that this issue was already discussed, however, it is not clear to me whether this was indeed addressed by a FieldTrip function. Below is the link about the question I was referring to:


In case there is no such a function, could someone provide me a rough procedure that is methodologically acceptable in the scientific community to compensate for this issue?

I am interested both in conceptual and implementational aspects. I would like to compare TFR or WPLI measures between two conditions and use non-parametric cluster-based permutation test for statistical analysis. My data is characterized by a within-subjects design, in case this is relevant information.

Thanks for your input in advance,

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