Dear Kenji,
the easiest way if you only have two time points is to work with the difference images in a cross-sectional design. You can use the function cat_stat_diff for that purpose. Then you can use a simple regression design (or in an interaction if you have more than one group) with your clinical variable.
Best,
Christian
On Thu, 7 Apr 2022 11:01:04 +0900, Kenji Yoshimura <[log in to unmask]> wrote:
>Dear SPM experts and Christian,
>
>I'm analyzing longitudinal SBM analysis of Parkinson's disease patients.
>Subjects underwent 2 time points (baseline and 2 years after) evaluations,
>and images were preprocessed using longitudinal segment pipeline in CAT12.
>
>I'd like to perform a regression analysis between the degree of cortical
>thinning and the continuous clinical variable that does not change over
>time (such as age at baseline, TIV, or education years).
>To do this, how can I construct a design matrix? Flexible factorial design
>would work for this purpose, but CAT12 manual says "Don't use covariates
>that don't change over time such as sex or TIV. These are ignored in the
>statistical analysis". I'm not sure how to set covariates and contrasts.
>
>Thanks in advance,
>Best regards.
>
>=============================================
>Graduate School of Medicine, Kyoto University
>Kenji Yoshimura M.D.
>54 Shogoin-Kawahara-cho
>Sakyo-ku, Kyoto, Japan
>606-8507
>TEL: 075-751-3773
>FAX: 075-753-4257
>Mail: [log in to unmask]
>=============================================
>
|