Nearly every test for normality is susceptible to finding that the distribution is "not normal" once the sample size is large enough. Random variation will guarantee that. As a result, the QQ plot is far better in determining if assumptions are met. Also, remember that the assumption of normality in ANOVA applies to the residuals and not the variables themselves, so be sure what you use as input into PROC UNIVARIATE are the residuals from your ANOVA. Finally, recall that ANOVA is robust to most assumptions, especially with large samples, so minor deviations from normality or homoskedasticity will not greatly influence the outcome.
Steve Denham
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