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Dear Cyril, I'm not sure I understand the question. So I will answer a different but possibly related one ! If regressors A and B are correlated then you can test for what they explain together using a [1 0; 0 1] F-contrast and what each explains *over and above what is explained by the other* using a t-contrast [1 0] and [0 1]. The issue of correlated variables is perhaps best dealt with by thinking about statistical tests rather than parameter estimates. Best, Will. cyril pernet wrote: > Dear Will, > > Sorry to bother you directly but I didn't get any answers from a > previous post and indeed you may be one of the few people how can help > me ... > I was wondering how the GLM is performed when fitting dummy and > continuous variables - say by hand without convolution, something easy. > The regression coefficients of continuous variables are unchanged > whether I fit a whole model that include dummy (1-1) variables and > continuous variables or only those continuous variables - by contrast > the coef of the dummy variables are different between the full model and > a model with only dummy variables - is there any particular way to do > the fit? > > thank you for your help > cyril > > > -- William D. Penny Wellcome Trust Centre for Neuroimaging University College London 12 Queen Square London WC1N 3BG Tel: 020 7833 7475 FAX: 020 7813 1420 Email: [log in to unmask] URL: http://www.fil.ion.ucl.ac.uk/~wpenny/