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Hallo, may I ask what is permuted, the explanatory variable of interest alone, or the variable of interest and nuisance covariates? I would think that only the variable of interest should be permuted, but I would be interested to hear if there is a rationale for permuting variables of interest and covariates together, or if anyone has strong opinions in one or the other direction. We are currently using permutation tests in the statistical analysis of our data, and permute the variable of interest only, so my question also has a practical relevance. If no one cares, then we'll keep using our approach. Thanks a lot, Roberto Viviani Dept. of Psychiatry University of Ulm, Germany Quoting Thomas Nichols <[log in to unmask]>: > Dear Johanna, > > No, currently the paired t-test plug-in in SnPM doesn't allow for nuisance > covariates. However, a paired t-test is equivalent to a one-sample t-test > on the pairwise differences, and the One Sample T-test plug-in *does* allow > for nuisance (or "confounding") covariates. > > The attached script, PairDiff.m will produce the differences if you don't > already have them. Let me know if it works for you OK. > > Sorry for the trouble. > > -Tom > > On Mon, Mar 31, 2008 at 11:13 AM, Scheuerecker, Johanna < > [log in to unmask]> wrote: > >> Dear SPMers, >> >> does anyone know if there is a possibility to use paired t-test in SNPM5 >> with one covariate of interest? >> >> >> Thanks a lot, >> >> Johanna >> > > > > -- > ____________________________________________ > Thomas Nichols, PhD > Director, Modelling & Genetics > GlaxoSmithKline Clinical Imaging Centre > > Senior Research Fellow > Oxford University FMRIB Centre >