control variables / cfg.cvar

Eric Maris e.maris at DONDERS.RU.NL
Fri Jul 23 01:28:59 CEST 2010


Dear Michael,



> So in my design I have two levels of the control variable: L1 are
> subjects with c1-R/c2-L pairing and L2 are subjects with c1-L/c2-R
> pairing (?). If I now permute only within the levels (which I would do
> anyway if I used a dependend samples test?) then still there are
> perumtations where response hands are sorted on the two sets to be
> compared, giving rise to large unwanted clusters in this particular
> permutation and other that are similar to it.  Sure, this will not
> result in false positives, but decrease the sensitivity of my
> experiment.
> 
> But maybe I misunderstand the meaning of  "permuting the data sets
> (single trials or subject averages) within each of the  levels of the
> control variable" . Does a permutation within the levels mean, I
> permute left hand responses only with left hand repsonses and right
> hand responses only with right hand responses? In this case I would
> have to give up my dependend samples testing (within subjcets) and use
> independent samples testing (across) subjects, because I can only
> exchange left hand responses in condition 1 and left hand responses in
> condition 2 between subjects, correct?


An example should be able to clarify things. Control variables are especially useful in between-subject and (single subject) between-trials studies. Let's consider a between-subjects study in which our interest is in assessing the effect of some individual difference variable, such as two different alleles of some gene. Assume that dependent variable strongly depends on age. In that case, sensitivity wrt identifying the genetic effect could be increased (as compared with an analysis without the age variable) by making a number of fairly homogenous age groups, and to perform a permutation test by randomly permuting the two alleles WITHIN each of these age groups. 

I found it hard to use your example to illustrate the usefulness of permutation within the levels of a control variable. Probably, I'm missing a point here. Maybe you can help me by pointing out what is the independent variable whose effect you want to assess and which other variable (the control variable) is also responsible for variance in the dependent variable, but in whose effect you are not interested.

Best,

Eric







> 
> Thanks for your help on this,
> Michael
> 
> ----------------------------------
> The aim of this list is to facilitate the discussion between users of
> the FieldTrip  toolbox, to share experiences and to discuss new ideas
> for MEG and EEG analysis. See also
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> http://www.ru.nl/neuroimaging/fieldtrip.

----------------------------------
The aim of this list is to facilitate the discussion between users of the FieldTrip  toolbox, to share experiences and to discuss new ideas for MEG and EEG analysis. See also http://listserv.surfnet.nl/archives/fieldtrip.html and http://www.ru.nl/neuroimaging/fieldtrip.



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