SAS/STAT Software

Post Processing

The SAS/STAT post processing procedures enable you to perform hypothesis tests, compute confidence intervals, produce prediction plots, and score new data sets.

The SAS/STAT post processing procedures include the following:

PLM Procedure

The PLM procedure performs postfitting statistical analyses for the contents of a SAS item store that was previously created with the STORE statement in some other SAS/STAT procedure. An item store is a special SAS-defined binary file format used to store and restore information with a hierarchical structure. The following are highlights of the PLM procedure's features:

  • performs custom hypothesis tests
  • computes confidence intervals
  • produces prediction plots
  • scores a new data set
  • enables you to filter the results
  • offers the most advanced postprocessing techniques available in SAS/STAT including the following:
    • step-down multiplicity adjustments for p-values
    • F tests with order restrictions
    • analysis of means (ANOM)
    • sampling-based linear inference based on Bayes posterior estimates
For further details, see PLM Procedure

SCORE Procedure

The SCORE procedure multiplies values from two SAS data sets, one containing coefficients (for example, factor-scoring coefficients or regression coefficients) and the other containing raw data to be scored by using the coefficients from the first data set. The result of this multiplication is a SAS data set that contains linear combinations of the coefficients and the raw data values. The following are highlights of the SCORE procedure's fetaures:

  • automatically standardizes or centers the variables from the raw data for you, based on information from the original variables and analysis from the coefficients data set
  • performs BY group processing, which enables you to obtain separate scoring for grouped observations
For further details, see SCORE Procedure