The HPMIXED Procedure

Syntax: HPMIXED Procedure

The following statements are available in the HPMIXED procedure:

  • PROC HPMIXED <options>;

  • BY variables;

  • CLASS variable <(REF= option)> …<variable <(REF= option)>> </ global-options>;

  • EFFECT name=effect-type (variables </ options>);

  • ID variables;

  • MODEL dependent = <fixed-effects> </ options>;

  • RANDOM random-effects </ options>;

  • REPEATED repeated-effect </ options>;

  • PARMS <(value-list)…> </ options>;

  • TEST fixed-effects </ options>;

  • CONTRAST ’label’ contrast-specification <, contrast-specification> <, …> </ options>;

  • ESTIMATE ’label’ contrast-specification <(divisor=n)><, ’label’ contrast-specification <(divisor=n)>> <, …> </ options>;

  • LSMEANS fixed-effects </ options>;

  • NLOPTIONS <options>;

  • OUTPUT <OUT=SAS-data-set><keyword<(keyword-options)> <=name>> …<keyword<(keyword-options)> <=name>> </ options>;

  • WEIGHT variable;

Items within angle brackets ( < > ) are optional. The CONTRAST, ESTIMATE, LSMEANS, RANDOM, and TEST statements can appear multiple times; all other statements can appear only once.

The PROC HPMIXED and MODEL statements are required, and the MODEL statement must appear after the CLASS statement if these statements are included. The BY, CLASS, MODEL, ID, OUTPUT, TEST, RANDOM, REPEATED and WEIGHT statements are described in full after the PROC HPMIXED statement in alphabetical order. The EFFECT, is shared with many other procedures. Summary descriptions of functionality and syntax for this statement is also given after the PROC HPMIXED statement in alphabetical order, but you can find full documentation on it in Chapter 20, Shared Concepts and Topics.

Table 1 summarizes the basic functions and important options of each PROC HPMIXED statement.

Table 1: Summary of PROC HPMIXED Statements

Statement Description Options
PROC HPMIXED Invokes the procedure DATA= specifies input data set, METHOD= specifies estimation method
BY Performs multiple PROC HPMIXED analyses in one invocation None
CLASS Declares qualitative variables that create indicator variables in design matrices None
ID Lists additional variables to be included in predicted values tables None
MODEL Specifies dependent variable and fixed effects, setting up bold upper X S requests solution for fixed-effects parameters, DDFM= specifies denominator degrees of freedom method
RANDOM Specifies random effects, setting up bold upper Z and bold upper G SUBJECT= creates block-diagonality, TYPE= specifies covariance structure, S requests solution for random-effects parameters
REPEATED Sets up bold upper R SUBJECT= creates block-diagonality, TYPE= specifies covariance structure, R= displays estimated blocks of bold upper R, GROUP= enables between-subject heterogeneity
PARMS Specifies a grid of initial values for the covariance parameters HOLD= and NOITER hold the covariance parameters or their ratios constant, PARMSDATA= reads the initial values from a SAS data set
CONTRAST Constructs custom hypothesis tests E displays the bold upper L matrix coefficients
ESTIMATE Constructs custom scalar estimates CL produces confidence limits
LSMEANS Computes least squares means for classification fixed effects DIFF computes differences of the least squares means, CL produces confidence limits, SLICE= tests simple effects
WEIGHT Specifies a variable by which to weight bold upper R None


Last updated: December 09, 2022