The HPLMIXED Procedure

PROC HPLMIXED Features

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.