Hi, I've got skewed data and have done what I can to normalise the data with little success. I wanted to know in terms of Non-para alternatives what I could run within SPSS to get results for the data.
Unfortunately I've looked at the Studentized Residuals and they contain Outliers. The Normal Q-Q Plots are not normal either. I've attempted to transform the data using LOG10 but it makes the data much harder to interpret.
I am not sure if it would be adequate to log transform the whole dataset because of some outliers, or whether ouliers are adequately dealt with using log transformation, or - as you mention yourself - how log transformed could be interpreted within the context of your research. Unfortunately I forgot to ask about the topic of your research and what the dependent variable actually does represent, since dealing with outliers is not a pure technical question, but depends strongly on content.
I suppose that with n=94 and equal groups, outliers do not affect assumptions (maybe someone wants to correct me here), but perhaps results. You could perform your split plot ANOVA with the untransformed data, and for checking robustness you could then repreat the analysis without extreme outliers. Or, if you have a substantial knowledge about the processes which produce the outliers, you could incorporate them into your model.