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Hi folks - How would one go about computing a standardized beta weight (in the regression sense) from a cope or pe? If I am correct, the pe's are (unstandardized) regression weights (b's). Therefore, I'd need to multiply by the standard deviation of the predictor and divide by the standard deviation of the data. But I am unsure which files would correspond to this. The varcope seems to be not just be the deviation of the predictor, as that should be the same for all voxels. It also isn't the standard deviation of the data, as this would be the same for all predictors. Is it a ratio of the two? If that is the case, then do I just divide the cope by the varcope to get a standardized weight? I'm not interested in getting percent signal change in this case ... it is a continuously varying parameter (from 0 to 1), so I'd like to get a beta weight (or even part correlation). Ed -- Ed Vessel U. of Southern California [log in to unmask] Dept. of Neuroscience HNB, 3641 Watt Way http://geon.usc.edu/~vessel Los Angeles, CA 90089-2520 (213) 740-6102