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**Testing for associations in longitudinal changes of structural connectivity and metric variables**Nov 12, 2022 03:11 PM | Marius Gruber

Testing for associations in longitudinal changes of structural connectivity and metric variables

Dear Andrew,

We are currently working on a longitudinal analysis with two time points (T1 and T2). We want to test the association between longitudinal changes in structural connectivity and longitudinal changes in a metric predictor, namely depression symptom severity (measured via Hamilton Depression Rating Scale).

Our first idea is to use a standard ANCOVA model to test the association between the difference in connectivity matrices (T2-T1) and the differences in HAMD scores (T2-T1) while correcting for baseline values of age and sex. For two participants with HAMD scores 15 and 20 at T1 and 6 and 10 at T2, our design matrix would look like this:

1 -9 35 0

1 -5 22 1

with the first column modeling the intercept, the second column modeling the difference in HAMD scores, the third column modeling the age at baseline, and the fourth column modeling the participants' sex.

An alternative we thought of would be to use a repeated measures ACNOVA with a design matrix containing a constant (1), the time points (-1 or 1), and the interaction of time and either the HAMD score at T1 or the HAMD score at T2, and the columns that model each participant's random intercept. For two participants with HAMD scores 15 and 20 at T1 and 6 and 10 at T2, our design matrix would look like this:

1 -1 -15 1 0

1 -1 -20 0 1

1 1 6 1 0

1 1 10 0 1

Is the second design matrix correctly specified in this way? And which of the two alternatives would be more sensible in your view?

Thank you very much in advance!

Marius

We are currently working on a longitudinal analysis with two time points (T1 and T2). We want to test the association between longitudinal changes in structural connectivity and longitudinal changes in a metric predictor, namely depression symptom severity (measured via Hamilton Depression Rating Scale).

Our first idea is to use a standard ANCOVA model to test the association between the difference in connectivity matrices (T2-T1) and the differences in HAMD scores (T2-T1) while correcting for baseline values of age and sex. For two participants with HAMD scores 15 and 20 at T1 and 6 and 10 at T2, our design matrix would look like this:

1 -9 35 0

1 -5 22 1

with the first column modeling the intercept, the second column modeling the difference in HAMD scores, the third column modeling the age at baseline, and the fourth column modeling the participants' sex.

An alternative we thought of would be to use a repeated measures ACNOVA with a design matrix containing a constant (1), the time points (-1 or 1), and the interaction of time and either the HAMD score at T1 or the HAMD score at T2, and the columns that model each participant's random intercept. For two participants with HAMD scores 15 and 20 at T1 and 6 and 10 at T2, our design matrix would look like this:

1 -1 -15 1 0

1 -1 -20 0 1

1 1 6 1 0

1 1 10 0 1

Is the second design matrix correctly specified in this way? And which of the two alternatives would be more sensible in your view?

Thank you very much in advance!

Marius

## Threaded View

Title | Author | Date |
---|---|---|

Marius Gruber |
Nov 12, 2022 | |

Andrew Zalesky |
Nov 14, 2022 | |