you could try coding genotype as 0,1,2 (missing, heterozygous, homozygous) instead of coding as discrete factors.
n.
On Wed, 2009-12-02 at 12:54 -0500, Stefan Brauns wrote:
Hi there,
we would like to test the effect of a binary variable (genotype = carrier vs. homozygous) on cortical thicknes in mri-glmfit. Since we are also controlling for gender and aquisition site (4 sites) we already have 16 groups. In order to control for age as a covariate we need at least 2 subjects per group to be able to estimate an age slope.
If we include the aforementioned binary variable (genotype) as a factor (two different "groups"), we would have 32 groups and unfortunately not enough subjects per group.
Is it possible to include binary variables ("dummy variable" coded as 0 and 1) such as genotype or gender as covariates (slope), in order to reduce the number of groups and examine the effect on thickness? In simple regression this would not affect the results - what would we expect here?
Many thanks,
Stefan
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer