In most neuroimaging, people use p<.01 (sig threshold > 2). It is more 
important to have a more stringent threshold when using gaussian random 
fields because the assumptions built into it. Since we use simulations 
directly, we don't have problems with those assumptions and so I think 
you can go down to p<.05 (sig>1.3). Other than that, there are not good 
guidelines.

On 4/13/16 8:36 AM, Clara Kühn wrote:
> Hi Doug,
>
> thanks for your reply. It made things a lot clearer. I totally understand 
> that you're probably receiving more than one cry for help per day.
>
> What would you say are the conventions for picking a threshold for analyses 
> on structural data?
>
> Cheers, Clara
>
> ----- Ursprüngliche Mail -----
> Von: "Douglas N Greve" <[email protected]>
> An: [email protected]
> Gesendet: Mittwoch, 13. April 2016 00:15:41
> Betreff: Re: [Freesurfer] REPOST: Monte Carlo correction in QDEC
>
> sorry, I could have sworn that I answered this one
>
> On 04/12/2016 08:57 AM, Clara Kühn wrote:
>> Dear FreeSurfer experts,
>>
>> for the analysis in QDEC I created my own Monte Carlo correction.
>> My questions relate to the threshold option.
>>
>> 1. Would I use neg if I have mostly blue clusters in the QDEC display and 
>> pos if I have mostly red clusters?
> No, you would use neg when you have an apriori assumption that your
> effect is going to be negative. Once you look at the results, it is no
> long apriori
>> 2. When do I use abs?
> If you do not have an apriori assumption about the sign of the effect
>> 3. I compared the neg option at different thresholds (1.3, 2.0 and 2.3) and 
>> I get different clusters:
>> 1.3 (=.05)
>> # ClusterNo  Max   VtxMax   Size(mm^2)  MNIX   MNIY   MNIZ    CWP    CWPLow  
>>   CWPHi   NVtxs   Annot
>>      1       -2.669   76591   1148.00     -6.7   14.5   62.7  0.00880  
>> 0.00760  0.01000  1600  superiorfrontal
>>      2       -2.443   91912   2128.78    -10.3   55.3  -23.5  0.00010  
>> 0.00000  0.00020  2971  medialorbitofrontal
>>
>> 2.0 (=.01)
>> # ClusterNo  Max   VtxMax   Size(mm^2)  MNIX   MNIY   MNIZ    CWP    CWPLow  
>>   CWPHi   NVtxs   Annot
>>      1       -3.289   92754    420.03    -36.5   57.0  -21.0  0.02140  
>> 0.01960  0.02330   571  parsorbitalis
>>      2       -2.669   76591    428.11     -6.7   14.5   62.7  0.01940  
>> 0.01760  0.02120   604  superiorfrontal
>>
>> 2.3 (=.005)
>> # ClusterNo  Max   VtxMax   Size(mm^2)  MNIX   MNIY   MNIZ    CWP    CWPLow  
>>   CWPHi   NVtxs   Annot
>>      1       -3.289   92754    314.80    -36.5   57.0  -21.0  0.01900  
>> 0.01730  0.02080   410  parsorbitalis
>>
>> Technically, if parsorbitalis is significant at .01 and .005, shouldn't it 
>> also be significant at .05? I've compared the clusters in freeview and the 
>> superiorfrontal is the same cluster in both 1.3 and 2.0. The parsorbitalis 
>> and the medialorbitofrontal clusters are completely different, not even 
>> closely overlapping.
> You are confusing the two types of thresholds. The voxel-wise threshold
> that you are changing defines what is and is not a cluster. As you
> change it clusters will change size. As you make it more liberal, you
> make it more likely that you see a cluster of a certain size by chance
> (ie, the p-value for the cluster gets worse). So as you make the
> threshold more liberal, there are two competing effects: (1) the cluster
> gets bigger, and (2) the p-value of a cluster of a given fixed size gets
> worse. If the cluster size does not increase enough to overcome the
> second effect, then the cluster p-value will get worse. It is just very
> complicated.
>
>> Do you have any idea why that is and what it does differently?
>> Thank you!
>> Cheers, Clara
>> _______________________________________________
>> Freesurfer mailing list
>> [email protected]
>> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
>>
>>

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