The HPLMIXED Procedure


PROC HPLMIXED provides easy accessibility to numerous mixed linear models that are useful in many common statistical analyses.

Here are some basic features of PROC HPLMIXED:

  • covariance structures, including variance components, compound symmetry, unstructured, AR(1), Toeplitz, and factor analytic

  • MODEL, RANDOM, and REPEATED statements for model specification as in the HPLMIXED procedure

  • appropriate standard errors, t tests, and F tests for all specified estimable linear combinations of fixed and random effects

  • a subject effect that enables blocking

  • REML and ML (maximum likelihood) estimation methods implemented with a variety of optimization algorithms

  • capacity to handle unbalanced data

  • special dense and sparse algorithms that take advantage of distributed and multicore computing environments

Because the HPLMIXED procedure is a high-performance analytical procedure, it also does the following:

  • enables you to run in distributed mode on a cluster of machines that distribute the data and the computations

  • enables you to run in single-machine mode on the server where SAS is installed

  • exploits all the available cores and concurrent threads, regardless of execution mode

For more information, see the section Processing Modes in Chapter 3: Shared Concepts and Topics.

PROC HPLMIXED uses the Output Delivery System (ODS), a SAS subsystem that provides capabilities for displaying and controlling the output from SAS procedures. ODS enables you to convert any output from PROC HPLMIXED into a SAS data set. See the section ODS Table Names.