help > Correlations
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Feb 2, 2018 11:02 PM | Lucas Moro
Correlations
Hi!
Given two groups coded as "patients" and "controls" and "patients_rating" and "controls_ratings" (symptoms scores), what is the difference between:
Selected only "patients_rating" in between subject contrast: 1 (effect of patients rating)
or "patients_rating" and "patients": 1 0 (simple main effect of patients_rating")?
Both -1 1 in between-condition contrast (post>pre).
The question is what is the correlation between the post-pre difference in connectivity of a seed (seed-to-voxel) and symptoms for patients.
I would appreciate your comments on that.
Best,
Lucas
Given two groups coded as "patients" and "controls" and "patients_rating" and "controls_ratings" (symptoms scores), what is the difference between:
Selected only "patients_rating" in between subject contrast: 1 (effect of patients rating)
or "patients_rating" and "patients": 1 0 (simple main effect of patients_rating")?
Both -1 1 in between-condition contrast (post>pre).
The question is what is the correlation between the post-pre difference in connectivity of a seed (seed-to-voxel) and symptoms for patients.
I would appreciate your comments on that.
Best,
Lucas
Feb 14, 2018 11:02 AM | Alfonso Nieto-Castanon - Boston University
RE: Correlations
Hi Lucas,
The latter is typically the correct way to evaluate the correlation between the post-pre differences in connectivity and symptom scores (selecting "patient_ratings" and "patients" and entering a [1 0] contrast). The former (selecting only "patient_ratings" and entering a [1] contrast value instead) is missing the intersect/constant term, and that is typically incorrect unless you have good reason to believe that the intersect of the above regression should be zero (e.g. if you want your model to assume that connectivity differences will be zero for those patients with patient_ratings equal to zero)
Hope this helps
Alfonso
Originally posted by Lucas Moro:
The latter is typically the correct way to evaluate the correlation between the post-pre differences in connectivity and symptom scores (selecting "patient_ratings" and "patients" and entering a [1 0] contrast). The former (selecting only "patient_ratings" and entering a [1] contrast value instead) is missing the intersect/constant term, and that is typically incorrect unless you have good reason to believe that the intersect of the above regression should be zero (e.g. if you want your model to assume that connectivity differences will be zero for those patients with patient_ratings equal to zero)
Hope this helps
Alfonso
Originally posted by Lucas Moro:
Hi!
Given two groups coded as "patients" and "controls" and "patients_rating" and "controls_ratings" (symptoms scores), what is the difference between:
Selected only "patients_rating" in between subject contrast: 1 (effect of patients rating)
or "patients_rating" and "patients": 1 0 (simple main effect of patients_rating")?
Both -1 1 in between-condition contrast (post>pre).
The question is what is the correlation between the post-pre difference in connectivity of a seed (seed-to-voxel) and symptoms for patients.
I would appreciate your comments on that.
Best,
Lucas
Given two groups coded as "patients" and "controls" and "patients_rating" and "controls_ratings" (symptoms scores), what is the difference between:
Selected only "patients_rating" in between subject contrast: 1 (effect of patients rating)
or "patients_rating" and "patients": 1 0 (simple main effect of patients_rating")?
Both -1 1 in between-condition contrast (post>pre).
The question is what is the correlation between the post-pre difference in connectivity of a seed (seed-to-voxel) and symptoms for patients.
I would appreciate your comments on that.
Best,
Lucas
Feb 14, 2018 12:02 PM | Lucas Moro
RE: Correlations
Hi Alfonso,
this is well explained! Thank you very much.
Greetings,
Lucas
this is well explained! Thank you very much.
Greetings,
Lucas