I've done some reading and it appears that there are a batch of different 'robust' methods, involving winsorized means/bootstrapping/rank-procedures that can apparently be used for such purposes. This seems fine but my problem is how to implement these methods.

I usually use SPSS for data analysis, but it does not provide a way of implementing these methods. From what I've read the R software appears to be the way to go. At my institution we have version 2.1.2. However I can't find a clear description of what code I should run to implement this analysis. I've got a copy of Wilcox 'Robust Estimation and Hypothesis Testing' but it's a bit over my head, and also appears to only talk about one-way repeated measures and then mixed designs, but misses out 2-way designs that are purely repeated measures. This is a problem I have found with a lot of the texts available for R, presumably because they are written with medical research in mind, where there is generally at least 1 between-subjects factor (i.e. treatment group vs control group).

Can anyone give me some straightforward advice as to how I can run a non-parametric 2x2 repeated measures analysis in R? Bear in mind that I have no real experience of R.

Thanks

RH