I have used PROC MIXED to fit a repeated measures spatial model to some spectrogram data (i.e. time-frequency representations). The datasets are quite large, 10800 data points. Following the advice stom Steve Denham in an earlier post, I checked the distribution of residuals. Despite looking like a very nice gaussian distribution, the skew is -0.016 and kurtosis 1.347. The Kolmogorov-Smirnov D test = 0.0185 Pr > D <0.0100. So, strictly speaking this distribution departs significantly from normal. I assume that the reason for this has more to do with the (relatively) large sample, and that I probably should not worry. Nevertheless, being a worrier i would really appreciate some advice. Many thanks in advance Piers_C
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