you have to make decisions about which interactions you want to model
On 11/9/18 8:43 AM, Worker, Amanda wrote:
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Yes. I just want to use 7 of those variables as predictors and 2 as covariates
of no interest in a linear regression model
________________________________
From:
freesurfer-boun...@nmr.mgh.harvard.edu<mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
<freesurfer-boun...@nmr.mgh.harvard.edu><mailto:freesurfer-boun...@nmr.mgh.harvard.edu>
on behalf of Greve, Douglas N.,Ph.D.
<dgr...@mgh.harvard.edu><mailto:dgr...@mgh.harvard.edu>
Sent: 08 November 2018 18:03:16
To: freesurfer@nmr.mgh.harvard.edu<mailto:freesurfer@nmr.mgh.harvard.edu>
Subject: Re: [Freesurfer] Multivariable linear regression with binary variables
You'd have 512 groups total, which is probably way too many regardless
of whether you do so manually or automatically. You need to think about
how you want to model all those variables since modeling all possible
interactions is not going to be possible.
On 11/08/2018 12:45 PM, Worker, Amanda wrote:
>
> External Email - Use Caution
>
> Hi,
>
>
> I am trying to run a multivariable GLM with mri_glmfit and I am
> currently setting up my fsgd file. I have 9 binary variables and 1
> continuous variable. My understanding is that in the fsgd file, my
> "class" would be every possible combination of these binary variables
> - which is a lot (hundreds) and setting this up manually doesn't seem
> reasonable. Is this correct and if so could you recommend another way
> to run this analysis?
>
>
> Thanks,
>
>
> Amanda
>
>
>
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