Hi Jenessa,

Jenessa Price wrote:
> I'm examining differences in cortical thickness in a sample of drug 
> users and non-users.  From the literature, it appears that the 2 
> covariates I should use for the GLM analysis will be gender and age.  
> Other researchers have examined other possible covariates (like age of 
> first use, # past year uses, IQ, etc.) using correlations between 
> those variables and significant clusters that differed between 
> groups.  Is this the best way to go about translating a typical 
> regression model into the Freesurfer statistical package (especially 
> if I'm interested in dose-dependent relationships)?
The age,  gender, and eTIV (estimated Total Intracranial Volume)  are 
typically used as nuisance variables. If age of first use, etc, are 
dose-dependent and you're interested in a dose relationship, then I 
would include one. You can also include more than one and use an F-test.
>
> Also, how do you suggest controlling for total brain volume?  Other 
> researchers have performed univariate analyses between groups on TBV 
> controlling for age and gender, then examined mean cortical thickness, 
> but I'm not quite sure what the steps are for this.  Could someone 
> help me identify the best way to control for TBV (i.e., is there a way 
> to control from the first GLM analysis, or is this a possible 
> covariate to enter in to the analysis)?
Gender is a good way to control for TBV, since that is the biggest 
effect. You can also use the eTIV mentioned above to correct for head 
size. Note that this is a difference between head size and brain size as 
brain size can shrink with age (and maybe drug use?).

doug
>
> Thanks!
>
> -- 
> Jenessa S. Price, M.A.
> Graduate Student, Clinical Psychology and Neuropsychology
> University of Cincinnati
> Campus Representative, American Psychological Association of Graduate 
> Students (APAGS)
>
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