 |
 |
Hi Andreas, Yes, need be synchronised. NPC would be useful to combine results, as opposed to simply correct them across. In either case, need synchronisation. Note, though, that synchronised permutations will happen in these cases by default. There is an option named "-syncperms" but that is to force synchronisation for cases where it wouldn't be done by default (e.g., multiple tests with no correction and no combination). For multiple ICs, NPC could be an option to combine results of components that ended up split by the ICA algorithm, but that are believed or known to belong to the same network. However, since the ICA is spatial, the overlap between these to allow meaningful combination may be suboptimal. Perhaps the Tippett's combining function could be a good choice here (as opposed to the default, that is Fisher's). Hope this helps! All the best, Anderson On 22 June 2017 at 11:08, Andreas Bartsch <[log in to unmask]> wrote: > Hi there, > > please let me chime in with a question: > If we’d use palm in the context of dual regression to test multiple ICs > using multiple „pseudo“- modalities (using -i for each group IC) and > corrmod (and corrcon), should the permutation scheme be synchronized? > Should we use npc ? > Thanks! > Cheers, > Andreas > > Von: FSL - FMRIB's Software Library <[log in to unmask]> on behalf of > "Anderson M. Winkler" <[log in to unmask]> > Antworten an: FSL - FMRIB's Software Library <[log in to unmask]> > Datum: Donnerstag, 22. Juni 2017 um 19:42 > An: <[log in to unmask]> > Betreff: Re: [FSL] PALM : Synchronized permutations > > Hi Jay, > > Thanks for the comments. Please see below: > > On 20 June 2017 at 12:00, SUBSCRIBE FSL Jay <[log in to unmask]> wrote: > >> Hello Anderson Winkler, >> >> I am trying to read and understand your article "Non-Parametric >> Combination and Related Permutation Tests for Neuroimaging" specifically >> the idea behind performing synchronised permutations. I came across the >> following text in the article >> >> "Moreover, non-independence does not need to be explicitly modelled, >> either between observations, between partial tests, or across space for >> imaging data, thus making such tests applicable to a wide variety of >> situations." >> >> 1) I understand that dependency between the input modalities need not be >> modelled between partial tests. Then, why synchronised permutations is >> performed for all the partial tests? Why not non-synchronised permutations? >> > > It's precisely the synchronised permutation scheme that allows the > dependencies to be captured implicitly. By "synchronised" it is meant that > however the observations are reordered in a given permutation for one > modality, it is done exactly in the same way for the other(s). > > One way of stating this is that, as we permute, for each permutation we > ask: "what my test statistics would look like if my observed data were like > this?". Answering this question needs that the data is rearranged in the > same way for all modalities. > > The same applies to NPC and to FWER-correction using the distribution of > the maximum statistic (which is, in fact, a form of NPC too). > > >> 2) Why is the combining function not applied directly on the input >> modalities? What is the idea behind partial p-values? >> > > The combination is of the evidence for (or against) the null hypothesis, > and this is summarised by the test statistic and its p-value. Moreover, not > always it is meaningful to directly combine data that come in different > units, scales, or represent different physical quantities. How to combine, > for example, blood flow measured with PET and fractional anisotropy > measured with diffusion MRI? Combining evidence towards an hypothesis is > feasible, but these modalities can't trivially combined otherwise. > > Hope this helps! > > All the best, > > Anderson > > > >> >> Thank you for your time. >> Best wishes >> Jay >> > >