Dear FreeSurfers,
I am interested in examining interaction effects between two sets of classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or Male & Control vs. Male & Treatment), but can mri_glmfit be used to examine interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
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Yes, you just need to come up with the the contrast matrix taht tests what you want to test. If the contrast matrix has one row, then it's a t-test. If there are more than one, then it's an F test. You example is actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets of classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or Male & Control vs. Male & Treatment), but can mri_glmfit be used to examine interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail. _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
great, thanks!
Doug Greve greve@nmr.mgh.harvard.edu 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests what you want to test. If the contrast matrix has one row, then it's a
t-test. If there are more than one, then it's an F test. You example is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected
Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Is running a t-test contrast still valid if I don't have equal numbers in the four groups (Male Treatment, Male Control, Female Treatment, Female Control) or should I be running an F test instead?
Sasha
Doug Greve greve@nmr.mgh.harvard.edu 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests what you want to test. If the contrast matrix has one row, then it's a
t-test. If there are more than one, then it's an F test. You example is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected
Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail.
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Still valid.
Sasha Wolosin wrote:
Is running a t-test contrast still valid if I don't have equal numbers in the four groups (Male Treatment, Male Control, Female Treatment, Female Control) or should I be running an F test instead?
Sasha
Doug Greve greve@nmr.mgh.harvard.edu 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests what you want to test. If the contrast matrix has one row, then it's a
t-test. If there are more than one, then it's an F test. You example is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected
Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Hi Sasha--
There is an excellent statistical source on interactions of the sort you are interested in. It may help you in setting up your tests. The name of the book is "Interaction Effects in Factorial Analysis of Variance" by James Jaccard. It should be available at your library, but if not it only costs about $17. It may appear a bit dense at first, but it should make sense if you work through the examples.
Anthony
Doug Greve wrote:
Still valid.
Sasha Wolosin wrote:
Is running a t-test contrast still valid if I don't have equal numbers in the four groups (Male Treatment, Male Control, Female Treatment, Female Control) or should I be running an F test instead?
Sasha
Doug Greve greve@nmr.mgh.harvard.edu 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests what you want to test. If the contrast matrix has one row, then it's a
t-test. If there are more than one, then it's an F test. You example is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected
Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If you are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited. If you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail.
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-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422
In order to help us help you, please follow the steps in: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Is it possible to run an ANOVA or multiple linear regression in freesurfer?
Doug Greve greve@nmr.mgh.harvard.edu 4/25/2006 11:17 am >>>
Still valid.
Sasha Wolosin wrote:
Is running a t-test contrast still valid if I don't have equal
numbers
in the four groups (Male Treatment, Male Control, Female Treatment, Female Control) or should I be running an F test instead?
Sasha
Doug Greve greve@nmr.mgh.harvard.edu 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests
what you want to test. If the contrast matrix has one row, then it's
a
t-test. If there are more than one, then it's an F test. You example
is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected
Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If
you
are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited.
If
you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Yes, all ANOVAs are linear models. You just have to figure out what contrast matrix (or matrices) implement the hypothesis to test.
Sasha Wolosin wrote:
Is it possible to run an ANOVA or multiple linear regression in freesurfer?
Doug Greve greve@nmr.mgh.harvard.edu 4/25/2006 11:17 am >>>
Still valid.
Sasha Wolosin wrote:
Is running a t-test contrast still valid if I don't have equal
numbers
in the four groups (Male Treatment, Male Control, Female Treatment, Female Control) or should I be running an F test instead?
Sasha
Doug Greve greve@nmr.mgh.harvard.edu 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests
what you want to test. If the contrast matrix has one row, then it's
a
t-test. If there are more than one, then it's an F test. You example
is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and Treatment/Control. I know mri_glmfit can be used to run t-test comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface data)?
my FSGD file looks like this: GroupDescriptorFile 1 Class MaleTreatment Class MaleControl Class FemaleTreatment Class FemaleControl Input subjid1a MaleTreatment Input subjid1b FemaleTreatment Input subjid2a FemaleControl Input subjid2b MaleControl etc...
Thanks, Sasha
Sasha Wolosin Research Assistant Developmental Cognitive Neurology Kennedy Krieger Institute 707 N. Broadway Baltimore, MD 21205 ph: (443) 923-9270 wolosin@kennedykrieger.org
Disclaimer: The materials in this e-mail are private and may contain Protected
Health Information. Please note that e-mail is not necessarily confidential or secure. Your use of e-mail constitutes your acknowledgment of these confidentiality and security limitations. If
you
are not the intended recipient, be advised that any unauthorized use, disclosure, copying, distribution, or the taking of any action in reliance on the contents of this information is strictly prohibited.
If
you have received this e-mail in error, please immediately notify the sender via telephone or return e-mail.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
freesurfer@nmr.mgh.harvard.edu
-
Anthony Steven Dick -
Doug Greve -
Sasha Wolosin