[[FsgdExamples|Back to FSGD Examples]] ~+'''Two Groups (One Factor/Two Levels), Two Covariates'''+~ This models the input as two separate planes (DODS), one for each group. The two groups can be thought of as two levels of a single discrete factor. The covariates can be thought of as continuous factors (eg, Age and Weight). <> = FSGD File (g2v2.fsgd) = {{{ GroupDescriptorFile 1 Title OSGM Class Group1 Class Group2 Variables Age Weight Input subject1 Group1 30 100 Input subject2 Group2 40 120 }}} Nclasses = 2 <
> Nvariables = 2 <
> = Regressors (DODS) = Nregressors = Nclasses*(Nvariables+1) = 2*(2+1) = 6 <
> Regressor1: ones for subjects in Group 1, 0 otherwise. Codes intercept/mean for Group 1 <
> Regressor2: ones for subjects in Group 2, 0 otherwise. Codes intercept/mean for Group 2 <
> Regressor3: age for subjects in Group 1, 0 otherwise. Codes age slope for Group 1 <
> Regressor4: age for subjects in Group 2, 0 otherwise. Codes age slope for Group 2 <
> Regressor5: weight for subjects in Group 1, 0 otherwise. Codes weight slope for Group 1 <
> Regressor6: weight for subjects in Group 2, 0 otherwise. Codes weight slope for Group 2 <
> = Contrasts = The number of columns in each contrast matrix must be the same as the number of regressors (Nregressors). If there is only one row in the contrast matrix, then the result will be a t-test and will have a sign. Reversing the signs in the contrast matrix will only change the sign of the output, not its magnitude. If there is more than one row, the result will be an F-test and will be unsigned. == Contrast 1 group.diff.mtx == Null Hypothesis: is there a difference between the group intercepts? Is there a difference between groups regressing out the effect of age and weight? {{{ 1 -1 0 0 0 0 }}} This is a t-test with Group1>Group2 being positive (red/yellow). == Contrast 2 group-x-age.mtx == Null Hypothesis: is there a difference between the group age slopes regressing out the effect of weight? Note: this is an interaction between group and age. Note: not possible to test with DOSS. {{{ 0 0 1 -1 0 0 }}} This is a t-test with Group1>Group2 being positive (red/yellow). == Contrast 3 group-x-weight.mtx == Null Hypothesis: is there a difference between the group weight slopes regressing out the effect of age? Note: this is an interaction between group and weight. Note: not possible to test with DOSS. {{{ 0 0 0 0 1 -1 }}} This is a t-test with Group1>Group2 being positive (red/yellow). == Contrast 4 group-x-age-x-weight.mtx == Null Hypothesis: does Group1 differ from Group2 in age or weight? Is there an interaction between group, age, and weight? {{{ 0 0 1 -1 0 0 0 0 0 0 1 -1 }}} Note: this is an F-test (and hence unsigned). Reversing the signs will have no effect. == Contrast 5 g1g2.intercept.mtx == Null Hypothesis: does mean of group intercepts differ from 0? {{{ 0.5 0.5 0 0 0 0 }}} This is a t-test with (Group1+Group2)/2 > 0 being positive (red/yellow). If the mean is < 0, then it will be displayed in blue/cyan. == Contrast 6 g1g2.age.mtx == Null Hypothesis: does mean of group age slope differ from 0? Is there an average affect of age regressing out the effect of group and weight? {{{ 0 0 0.5 0.5 0 0 }}} This is a t-test with (Group1+Group2)/2 > 0 being positive (red/yellow). If the mean is < 0, then it will be displayed in blue/cyan. == mri_glmfit command == This is an example invocation of mri_glmfit. Depending upon your application, you may have other options as well. {{{ mri_glmfit \ --glmdir g2v2 \ --y y.mgh \ --fsgd g2v2.fsgd \ --C group.diff.mtx \ --C group-x-age.mtx \ --C group-x-weight.mtx \ --C group-x-age-x-weight.mtx \ --C g1g2.intercept.mtx \ --C g1g2.age.mtx }}}