Hi Gang-

Thanks very much for your input. This is very helpful. However, I have to admit, I am now a little confused. If the t scores are equivalent between scaled and unscaled, why go to the trouble of converting to percent signal change before group analysis? Why not just use the t score? (This is a little circular here--it is basically back to my original question "What's wrong with using the t (z) as a DV?").

As I understand it, the t is a measure of whether the parameter estimate (beta) is significantly different from zero. It is given basically as t = beta/standard error (beta). This has the effect of scaling because the t value means the same thing across subjects, and baseline is taken into account during the deconvolution. Higher t's mean better fit to the model. By the way, please correct me if I am wrong here.

If fit to the model is what you are interested in, why not calculate the average fit to the model and compare across conditions? I am kind of playing devil's advocate here, because something about using a test statistic as a DV seems wrong, but maybe fMRI analysis is different from a standard behavioral study in this respect.

Anthony

p.s. At some point I promise to quit beating a dead horse.