Exploring Outliers and Problematic Data Distributions

Numeric variable outliers (suspiciously extreme minimum or maximum values) may be apparent in the analysis above. But you should explore them further as demonstrated below, while also consulting with your data source and the literature to verify what are reasonable minimum and maximum values. Some variables will not meet the assumptions of statistical tests (for example, will not be normally distributed). The PROC UNIVARIATE code below will get us started with useful output for the variable FG, which is fasting blood glucose value.
ODS listing close; ODS rtf file="c:/temp/TIADout.rtf"; proc univariate data=TIAD; var FG; qqplot FG/normal(mu=est sigma=est color=red l=4) square; run; ODS rtf ...

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