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<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Dear FieldTrip list,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">I have a quick question about using “ft_freqgrandaverage” to calculate a group average of powerspectrum while ignoring missing channels across subjects.
<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Some subjects in my dataset have bad channels so I dropped these channels and replaced their values with NaNs instead of doing interpolation. However, “ft_freqgrandaverage” doesn’t seem to ignore
these NaNs while calculating the grand mean so I ended up with a lot of missing channels in my group average – is there a way for the function to ignore channels with NaNs? (I tried to use cfg.nanmean = 'yes' but it didn’t work).<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Thank you!<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif"><o:p> </o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Best,<o:p></o:p></span></p>
<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Anqi <o:p></o:p></span></p>
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