Thanks Doug, I have two follow-up questions.
1. I am using QDEC and my discrete variables are: (a) TYPE (PATIENTS/CONTROLS) and (b) GENDER I include age as a continous co-variate and then select all of the variable before running the design. I believe QDEC is generating the various possible contrast matrices and the corresponding research question. When I run QDEC, I see the following questions: A. Does the average thickness, accounting for Gender differ between Patients and Controls? B. Does the thickness-age correlation, accounting for Gender differ between Patients and Controls ? (I think this is looking at whether the slopes are different for the two groups) I was wondering why I dont see a question like "Does the average thickness, accounting for Gender *AND AGE* differ between Patients and Controls?" 2. It is likely I dont have a full understanding of the GLM theory. Could you please suggest some good references describing the GLM theory ? Thanks Mehul On Thu, Oct 29, 2009 at 10:57 AM, Douglas N Greve <gr...@nmr.mgh.harvard.edu > wrote: > > > Mehul Sampat wrote: > >> Hi FS folks, >> >> I have a basic GLM question. I went through the tutorials online but I was >> not sure and wanted to check with someone. >> >> I am trying to compare the cortical thickness between a group of patients >> (n = 166) and controls (n = 76). >> >> For patients mean age is 49.8 +/- 9.1 and there are 55 Male; 111 Female >> For controls mean age is 40.5 +/- 11.4 and there are 26 Male; 50 Female >> >> If include gender as a fixed factor does the output of the GLM answer the >> following: >> 1. "Is the cortical thickness different between the patients and controls >> accounting for gender" >> > All the factors in mri_glmfit/QDEC are random factors. But, yes, it would > answer that question. > > >> 2. As I understand the GLM setup one can control for gender and other >> discrete factors but not for continuous co-variates such as age ? >> That is one can find the association between thickness and age and see if >> it is different for the two groups. >> However if the age distributions for the two groups are different one >> cannot control for it with GLM. is this interpretation correct ? >> > Not quite. You can always put age in as a continuous covariate. If there > are effects of age or an interaction between age and group, then there are > some subtle statistical issues. > > doug > >> >> If so, how would one control for age in such an analysis ? >> >> Any help is much appreciated. >> >> Thanks >> Mehul >> >> >> >> >> 2. For the correction of multiple comparisons, when should one use FDR as >> compared to monte-carlo simulations ? >> >> Thanks >> Mehul >> >> ------------------------------------------------------------------------ >> >> _______________________________________________ >> Freesurfer mailing list >> Freesurfer@nmr.mgh.harvard.edu >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer >> > > -- > Douglas N. Greve, Ph.D. > MGH-NMR Center > gr...@nmr.mgh.harvard.edu > Phone Number: 617-724-2358 Fax: 617-726-7422 > > In order to help us help you, please follow the steps in: > surfer.nmr.mgh.harvard.edu/fswiki/BugReporting > > >
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