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Have you looked at this page MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples ? Bascially I think you will need number of classes = 2=M/F times N=#sights, then have age and age^2 as your continuous regressors. With the FSGD, you have a choice of a full interaction model (DODS=different offset different slope) or have each continuous variable be its own column. What you are describing would be a mixture of these things, so you would need to create your own design in that case. Eg, you could have a column for each class; the value=1 if that subject is in that class or 0 if not. Then you'd have a column for age^2, then you would have two columns for age, one would be the age if the subject is M otherwise 0, the other would be age if the subject is F otherwise 0. You can pass the matrix to mri_glmfit with the --X option (instead of using --fsgd).