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 MIXED 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 2: 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.