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.
Here are some basic features of PROC MIXED:
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covariance structures, including variance components, compound symmetry, unstructured, AR(1), Toeplitz, spatial, general linear, and factor analytic
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GLM-type grammar, by using MODEL, RANDOM, and REPEATED statements for model specification and CONTRAST, ESTIMATE, and LSMEANS statements for inferences
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appropriate standard errors for all specified estimable linear combinations of fixed and random effects, and corresponding t and F tests
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subject and group effects that enable blocking and heterogeneity, respectively
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REML and ML estimation methods implemented with a Newton-Raphson algorithm
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capacity to handle unbalanced data
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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 section ODS Table Names.
The MIXED procedure uses ODS Graphics to create graphs as part of its output. For general information about ODS Graphics, see Chapter 21: Statistical Graphics Using ODS. For specific information about the statistical graphics available with the MIXED procedure, see the PLOTS= option in the PROC MIXED statement and the section ODS Graphics.