Hi Hannah,

Rather than setting a threshold, you might want to consider summarazing your results according to the number of signficiant connections implicated for each network. For example, you might have 58% of connections within the DMN are implicated and 45% connection between the DMN and other networks are implicated. I would suggest not to put the threshold too low, since while this may detect statistically signifciant effects, the effect sizes will be low and possibly not meaningful from a practical perspective. Statistical signifciance does not imply practical/clinical signfiicance. 

andrew

Originally posted by Hannah Terborg:

Hi,

I have a question about-threshold selection.   I know that any choice of component forming t-threshold is rather arbitrary and does not affect specificity. It is often recommended, especially if the type of effect (small and strong vs wide and distributed) is unknown, to try a range of thresholds. I followed this advice for the analysis of my wPLI MEG connectivity data. This led to networks ranging from very dense to consisting of just one or two edges.  Do you have any advice on how to choose one network among all significant networks for interpretation and further analysis?

 

Best,

Hannah