Hi FSLrs,
We are doing analyses with TBSS and performed a regression analysis between cognitive functions and FA maps in patients and controls. We did a matrix with the next EV´s: one for the group of patients, other for the group of normal controls, other for the neuropsychological task (score in salthouse test) in patients and another for the neuropsychological task in normal controls. The correlation we obtained between patients’ FA maps and salthouse scores were significant. However, when we introduce age, gender, and years of education as covariates in the regression analyses this significant results disappear. The way we add the covariates to the design matrix was the following: We added two EV´s for gender (one for patients group and other for normal control), two EV´s for age (one for patients group and other for normal control) and another two EVs for years of education (one for patients group and other for normal control). In the contrasts we just put 0s in the covariates.
Is this the correct way of introducing confounding covariates in the matrix?
Is it possible to do include many covariates in a correlation analysis?
Thank you for your help!
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