Basic Features

The MIXED Procedure

Basic Features

PROC MIXED provides easy accessibility to numerous mixed linear models that are useful in many common statistical analyses. In the style of the GLM procedure, PROC MIXED fits the specified mixed linear model and produces appropriate statistics.

Some basic features of PROC MIXED are

covariance structures, including variance components, compound symmetry, unstructured, AR(1), Toeplitz, spatial, general linear, and factor analytic
GLM-type grammar, using MODEL, RANDOM, and REPEATED statements for model specification and CONTRAST, ESTIMATE, and LSMEANS statements for inferences
appropriate standard errors for all specified estimable linear combinations of fixed and random effects, and corresponding t- and F-tests
subject and group effects that enable blocking and heterogeneity, respectively
REML and ML estimation methods implemented with a Newton-Raphson algorithm
capacity to handle unbalanced data
ability to create a SAS data set corresponding to any table

PROC MIXED 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 of the output from PROC MIXED into a SAS data set. See the "Changes in Output" section.

Chapter Contents
Previous
Next
Top