Dear Katerina,
please can you provide an image of your design matrix. This warning only occurs if the model cannot correctly deal with the design or the nuisance parameters.
Best,
Christian
On Wed, 25 Nov 2020 13:08:47 +0000, Katerina Pappa (PGR) <[log in to unmask]> wrote:
>Dear Christian and CAT12 experts,
>
>I hope you are well.
>I built a separate model for the baseline data only to test for group effects as you suggested in a previous email (covariates TIV and age were included). I then tried to run the TFCE estimates with your toolbox (using default settings), but I got the following error:
>
>WARNING: Large discrepancy between parametric and non-parametric statistic found (cc=0.46939)! Please try a different method to deal with nuisance parameters.
>
>Could you please explain what this means?
>
>Many thanks in advance!
>
>Best Wishes,
>Katerina
>
>
>-----Original Message-----
>From: Christian Gaser <[log in to unmask]>
>Sent: 11 November 2020 22:01
>To: [log in to unmask]; Katerina Pappa (PGR) <[log in to unmask]>
>Subject: Re: CAT12 - longitudinal design, TFCE estimates
>
>Dear Katerina,
>
>On Tue, 10 Nov 2020 11:20:21 +0000, Katerina Pappa (PGR) <[log in to unmask]> wrote:
>
>>Dear SPM and CAT12 experts,
>>
>>I was hoping you could help with the following please.
>>
>>As described in Kurth et al. (2015) the TFCE approach (Smith & Nichols, 2009) is recommended in VBM analysis to account for the multiple comparison problem. I used the TFCE toolbox called within CAT12 and run the TFCE estimates for the different contrasts.
>>
>>When I tried to run the TFCE estimate for the main effect of group I encountered the following error:
>>"Please note that permutation is only done within subjects for repeated Anova. ERROR: No contrasts on subjects/block effects allowed."
>You are trying to test for group effects at one time point in a flexible factorial model for longitudinal data. This is not supported as a contrast for the TFCE toolbox. In your case I would suggest building a separate model for the baseline data only to test for group effects at baseline.
>
>>
>>Question 1:
>>Should I choose the TFCE method to perform corrections in my analysis or use the traditional p < 0.05 FWE at the cluster level (voxel level p < 0.001 uncorrected)?
>The cluster statistics is of course an alternative, but often less powerful compared to the TFCE.
>
>>
>>Question 2:
>>Does the TFCE method work only for within group comparisons?
>Yes, but not in a flexible factorial model.
>
>Best,
>
>Christian
>>
>>Thank you very much for your help!
>>
>>Best Wishes,
>>Katerina
>>
>>-----Original Message-----
>>From: Christian Gaser <[log in to unmask]>
>>Sent: 16 October 2020 13:58
>>To: Katerina Pappa (PGR) <[log in to unmask]>
>>Subject: Re: CAT12 - longitudinal design, flexible factorial model
>>
>>Dear Katerina,
>>
>>On 16 Oct 2020, at 10:37, Katerina Pappa (PGR) wrote:
>>
>>> -----Original Message-----
>>> From: Christian Gaser <[log in to unmask]>
>>> Sent: 16 October 2020 07:39
>>> To: [log in to unmask]; Katerina Pappa (PGR)
>>> <[log in to unmask]>
>>> Subject: Re: CAT12 - longitudinal design, flexible factorial model
>>>
>>> Dear Katerina,
>>>
>>> On Thu, 15 Oct 2020 10:10:02 +0000, Katerina Pappa (PGR)
>>> <[log in to unmask]> wrote:
>>>
>>>> Dear SPM and CAT12 experts,
>>>>
>>>> I am interested in exploring the structural changes following a
>>>> working memory training paradigm in healthy young adults.
>>>> Structural MRI was acquired over three time points, i.e. time 1:
>>>> pre-training, time 2: early training and time 3: post-training.
>>>> Participants were assigned into two groups, i.e. training group and
>>>> active control group.
>>>> I am using a sub-sample of the full dataset to try out the VBM
>>>> analysis.
>>>>
>>>> I have used the longitudinal option from the CAT12 toolbox to
>>>> conduct the pre-processing steps.
>>>> Following the CAT12 manual, I used a flexible factorial model with
>>>> factors: Subject (Factor 1), Group ( Factor 2, 2 levels) and Time
>>>> (Factor 3, 3 levels).
>>>>
>>>> Main effects and interactions to examine:
>>>> Main effect of Factor 2
>>>> Main effect of Factor 3
>>>> Interaction of Factors 2 by 3
>>>> Main effect of Factor 1
>>> Here the main effects of Factor 2 and 3 seem unnecessary. It's
>>> sufficient to model the main effect of Factor 1. Or are you not
>>> referring to the main and interaction effects you have to define to
>>> build your model ("Main effects & Interaction" in the flexible
>>> factorial batch)?
>>>
>>> Please follow the example in the CAT12 manual on page 40 for the
>>> design and page 44 for the contrasts.
>>>
>>> F-test
>>> For any differences in Time in Group A eye(k)-1/k
>>> For any differences in Time in Group B [zeros(k) eye(k)-1/k]
>>> For main effect Time [eye(k)-1/k
>>> eye(k)-1/k]
>>> For interaction Time by Group [eye(k)-1/k 1/k-eye(k)]
>>> For main effect Group [ones(1,k)/k
>>> -ones(1,k)/k ones(1,n1)/n1 -ones(1,n2)/n2]
>>> Effects of interest (for plotting) [eye(k)-1/k zeros(k);
>>> zeros(k) eye(k)-1/k]
>>>
>>> Here n1 and n2 are the number of subjects in Group A and B
>>> respectively and k is the number of time points.
>>>
>>> However, please also see here for a discussion by Martyn McFarquhar
>>> about inflating your statistical results by using the contrast for
>>> the main effect Group:
>>> https://www.jiscmail.ac.uk/cgi-bin/wa-jisc.exe?A2=SPM;ae98f7d5.2005
>>> https://www.frontiersin.org/articles/10.3389/fnins.2019.00352/full
>>>
>>> Best,
>>>
>>> Christian
>>>
>>>>
>>>> I used the weights as described in
>>>> http://www.sbirc.ed.ac.uk/cyril/download/Contrast_Weighting_Glascher
>>>> _ Gi telman_2008.pdf in order to define the contrasts. The main
>>>> effects and interactions work fine.
>>>>
>>>> However, when I set up the contrast for the main effect of condition
>>>> with a single regressor, e.g. time 3 in my study, as described in
>>>> design 3, contrast number 5, page 10 (Glascher & Gitelman), it's not
>>>> clear to me what this represents. See picture attached for details.
>>>>
>>>> Could you please assist with this?
>>>>
>>>> Many thanks for your help in advance!
>>>>
>>>> Best Wishes,
>>>> Katerina
>>>>
>>>>
>>
>>
>
>
|