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SAS/STAT software provides many powerful methods to fit general linear models with complicated effects. Some SAS/STAT procedures also enable one to estimate, test, compare, or plot functions of the estimated parameters. Such postprocessing can be as straightforward as predicting responses for given observations, or as complex as plotting multiplicity-adjusted comparisons of LS-means. In the past, extensive postprocessing facilities have been limited to a few procedures, such as the GLM and MIXED procedures. This paper discusses how the PLM procedure, new in SAS/STAT 9.22, works in conjunction with a new STORE statement in many familiar SAS/STAT procedures to provide a full complement of postprocessing features for a wide spectrum of linear models.
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