I am running an analysis were I want to control for age, sex, and education.
As suggested by Andrew, I simply added a column to my design matrix for each covariate and I added an extra zero to my contrast vector for each covariate added.
My study design has 2 groups (controls and patients) and 2 time points (two-way repeated measure ANCOVA).
Since the influence of the covariates on the controls is different from that on the patients over the time, I was wondering, if is possible to correct the covariates separately for each groups.
What about setting up the design matrix in NBS like this (in the example I put 3 subjects per group):
Age Patients/ Age Controls/ Education Patients/ Education Controls/ Sex Patients/ Sex Controls
34 0 9 0 1 0
53 0 12 0 -1 0
23 0 13 0 1 0
0 30 0 10 0 1
0 51 0 14 0 -1
0 22 0 13 0 1
Technically it works, but I don't know if it is correct.
Does NBS interpret this as a group-specific covariate and models it within the group or does NBS simply interprets it as zeros and modelled it across both groups?
Thank you in advance for any kind of advice.
Kind regards
Patrizia
Hi Patrizia
I am running an analysis were I want to control for age and
sex.
My study design has two groups (patients and controls) and I would
like to use age and gender as covariates to analyse the brain
network connections that differ between the two groups
What about setting up that part of the design matrix which models
the covariate in NBS like this (in the example I put 3 subjects per
group)
1 1 0 34
1 1 1 53
1 1 1 23
1 0 0 60
1 0 1 35
1 0 1 23
The first column represents the constant, the second column is the
group (1 for patient, 0 for control), the third column is the sex
(1 for male, 0 for female), and the fourth column is the gender,
which seems to be possible to design in this way as I looked
through the forum discussions, but I don't know if it is correct or
not
Finally how should I look at the main effect of the group and the
choice of the test（two-sample t-test？？？）。
Thank you in advance for any kind of advice.
Kind regards
Chenrukai
Age and gender are covariates, so your method is ANCOVA, not a t-test.