not possible with qdec On 09/16/2015 11:29 AM, pablo najt wrote: > > Dear Jorge, I am testing 3 groups (HC, BD, relative) and want to apply > your model. Now I am in doubt if I would be able to use qdec? Or if > this instead will not be viable as I have 3 groups is not possible > with qdec? > Thanks > Pablo > > ------------------------------------------------------------------------ > Date: Thu, 10 Sep 2015 13:44:36 +0000 > From: jbernal0...@yahoo.es > To: freesurfer@nmr.mgh.harvard.edu > Subject: Re: [Freesurfer] A mixed effect model approach in within > subject dataset > > Hi Pablo > > I think you can use LME to analyze your data by ordering the rows of > your design matrix appropriately. You can consider all subjects > belonging to the same family as if they were a single subject in a > longitudinal analysis. You can put in your design matrix all subjects > belonging to family1 first, then all subjects belonging to family 2 > and so on. Then the 'ni' required by lme_mass_fit_vw is a vector with > the number of subjects in each family as its entries (ordered > according to your design matrix). So the length of the 'ni' vector is > equal to the number of different families in your data. > > Now you can go further and additionally order the rows of your design > matrix within each family by age. This will allow you to test the > effect of age within family. > > When choosing the random effects for your statistical model remember > that a random effect can only be the intercept term or any covariate > that varies within family. For example you can compare a model with a > single random effect for the intercept term against the same model but > considering both the intercept term and age as random effects. > > Hope that helps > > Cheers > -Jorge > > > > ------------------------------------------------------------------------ > *De:* pablo najt <pablon...@hotmail.com> > *Para:* "freesurfer@nmr.mgh.harvard.edu" > <freesurfer@nmr.mgh.harvard.edu> > *Enviado:* Jueves 10 de septiembre de 2015 8:07 > *Asunto:* [Freesurfer] A mixed effect model approach in within > subject dataset > > Dear Freesurfer users, > I wanted to enquire if anyone had successfully been able to > implement Bernal's Linear Mixed Effects (LME) Models in > cross-section dataset *not longitudinal* (please see previous > thread below). I am willing to perform a LME (3 groups (HC, PT and > Unaffected_relatives) and 3 covariates (sex, age, and family) with > "family" variable been a within-subject factor. LME will allow to > control for the non-independence of data contributed by patients > and relatives from the same families. > Thanks in advance! > Pablo > > From: michaelnot...@hotmail.com > To: freesurfer@nmr.mgh.harvard.edu > Date: Wed, 19 Feb 2014 13:10:09 +0100 > Subject: [Freesurfer] Analysis of structural data acquired from > multiple sites by using a mixed effect model approach > > Hi everybody, > > I want to compare the surface data of 3 groups (GroupA, GroupB and > Controlls) but have the problem that they were acquired from 4 > different scanner sites. As I can see it, there are three ways how > I could tackle this problem: > > 1. I could use mri_glmfit and create a qdec table / fsgd-file with > 12 classes: Class GroupA_site1; Class GroupA_site2,... And then > use the contrasts [0.25 0.25 0.25 0.25 0 0 0 0 -0.25 -0.25 -0.25 > -0.25] to compare GroupA to the Controlls. My Problem with this > approach is, that the sites don't contribute the same amount of > subjects to the analysis. I'm not sure if this could be handled by > simply using a weighted contrast. Meaning, if Site1 and Site2 had > twice as many subjects than Site3 and Site4, I could modify the > contrast to [0.33 0.33 0.17 0.17 0 0 0 0 -0.33 -0.33 -0.17 -0.17]. > > 2. I could create dummy variables to account for the variability > between sites. In this case, I only need to specify 3 classes > (Class GroupA; Class GroupB; Class Controlls) in my fsgd-file. And > I use a design matrix that has 4 dummy variables at the end, which > specify to which site a subject belongs. This approach might work, > but I'm not confident that it is the right one. > > 3. I could use a mixed effect model approach and specify site as a > random effect. > > If I understand it correctly, the mixed effect model approach > would be the best one, as it accounts for the variability within > sites. Is that correct or are there other issues/better approaches? > > > I tried to implement a mixed effect model by using Bernal's Linear > Mixed Effects (LME) Models > (http://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels) > <http://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels%29> > but run into some problems. I'm not sure if LME can only be > applied on longitudinal data or if my implementation is wrong. I > have a design matrix X that specifies the characteristics of each > subject per row as follows: > > Intercept GroupA GroupB Controll Age IQ Site1 Site2 > Site3 Site4 > 1 1 0 0 11.1 99 0 0 1 0 > 1 0 1 0 11.1 101 0 0 1 0 > 1 1 0 0 11.4 95 1 0 0 0 > 1 0 0 1 12.4 100 1 0 0 0 > ... > > As I have no repeated measures, 'ni' is just a vector with length > X containing '1's. If I do now the vertex-wise linear > mixed-effects estimation, I get the following output: > > >> stats = lme_mass_fit_vw(X,[7 8 9 10],Y,ni,lhcortex); > Starting matlabpool using the 'local' profile ... connected to 8 > workers. > > Starting model fitting at each location ... > > Location 24994: Index exceeds matrix dimensions. > Location 24994: Algorithm did not converge. Initial and final > likelihoods: -10000000000, -10000000000. > Location 62484: Index exceeds matrix dimensions. > Location 62484: Algorithm did not converge. Initial and final > likelihoods: -10000000000, -10000000000. > ... > > I've checked the matrix dimensions of X, Y, ni and lhcortex and > compared them to the LME mass_univariate example stored in > ADNI_Long_50sMCI_vs_50cMCI.mat but couldn't find any divergence. > > Has anybody encountered similar problems? Is my approach of > specifying 'ni' as a vector of'1's even legitimate? > > Thanks, > Michael > > > _______________________________________________ Freesurfer mailing > list Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The > information in this e-mail is intended only for the person to whom > it is addressed. If you believe this e-mail was sent to you in > error and the e-mail contains patient information, please contact > the Partners Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to > you in error but does not contain patient information, please > contact the sender and properly dispose of the e-mail. > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu <mailto:Freesurfer@nmr.mgh.harvard.edu> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person to > whom it is > addressed. If you believe this e-mail was sent to you in error and > the e-mail > contains patient information, please contact the Partners > Compliance HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to > you in error > but does not contain patient information, please contact the > sender and properly > dispose of the e-mail. > > > > _______________________________________________ Freesurfer mailing > list Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The > information in this e-mail is intended only for the person to whom it > is addressed. If you believe this e-mail was sent to you in error and > the e-mail contains patient information, please contact the Partners > Compliance HelpLine at http://www.partners.org/complianceline . If the > e-mail was sent to you in error but does not contain patient > information, please contact the sender and properly dispose of the e-mail. > > _______________________________________________ Freesurfer mailing > list Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer The > information in this e-mail is intended only for the person to whom it > is addressed. If you believe this e-mail was sent to you in error and > the e-mail contains patient information, please contact the Partners > Compliance HelpLine at http://www.partners.org/complianceline . If the > e-mail was sent to you in error but does not contain patient > information, please contact the sender and properly dispose of the e-mail. > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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