[FieldTrip] effect sizes in M/EEG data

[Nina Kahlbrock]

Dear statistic experts,

 

I have a rather general question concerning effect sizes. I understand that
t-values give me an approximation of the effect size, as they state how big
the difference between two conditions is by taking into account the variance
and the number of observations. However, as I recall, effect sizes (like
Cohen’s d) are computed in order to find out how important the effect is,
independent of the number of observations. However, if I understand the code
correctly, dependent samples t-values are computed in a very similar way as
Cohen’s d (which is “the” value for effect sizes), both including the
variance and thus the number of observations in their functions.

In order to draw conclusions about the importance of the observed effect, is
it necessary to compute effect sizes like Cohen’s d or is it sufficient to
compute t-values as effect sizes for M/EEG data? If important to compute
effect sizes in a way different from t-values, does anyone know of a
function that computes effect sizes like that in FT?

 

Thank you in advance for your answer.

 

Best Regards,

 

Nina

 

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Nina Kahlbrock

Institute of Clinical Neuroscience and Medical Psychology 

Heinrich Heine University Duesseldorf

Universitaetsstr.  1

40225  Düsseldorf

 

Tel.:      +49 211 81 18075

Fax. .:   +49 211 81 19916

 

Mail:      <mailto:Nina.Kahlbrock at med.uni-duesseldorf.de>
Nina.Kahlbrock at med.uni-duesseldorf.de

 <http://www.uniklinik-duesseldorf.de/medpsychologie>
http://www.uniklinik-duesseldorf.de/medpsychologie

 

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