The HPLMIXED Procedure

Syntax: HPLMIXED Procedure

The following statements are available in PROC HPLMIXED.

  • PROC HPLMIXED <options>;

  • CLASS variables;

  • ID variables;

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

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

  • RANDOM random-effects </ options>;

  • REPEATED repeated-effect </ options>;

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

  • PERFORMANCE <options>;

Items within angle brackets ( < > ) are optional. The RANDOM statement can appear multiple times. Other statements can appear only once.

The PROC HPLMIXED and MODEL statements are required, and the MODEL statement must appear after the CLASS statement if a CLASS statement is included. The RANDOM statement must follow the MODEL statement.

Table 1 summarizes the basic functions and important options of the PROC HPLMIXED statements. The syntax of each statement in Table 1 is described in the following sections in alphabetical order after the description of the PROC HPLMIXED statement.

Table 1: Summary of PROC HPLMIXED Statements

Statement Description Important Options
PROC HPLMIXED Invokes the procedure DATA= specifies the input data set; METHOD= specifies the estimation method.
CLASS Declares qualitative variables that create indicator variables in bold upper X and bold upper Z 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 a solution for fixed-effects parameters.
RANDOM Specifies random effects, setting up bold upper Z and bold upper G SUBJECT= creates block-diagonality; TYPE= specifies the covariance structure; S requests a solution for the random effects.
REPEATED Sets up bold upper R SUBJECT= creates block-diagonality; TYPE= specifies the covariance structure.
OUTPUT Creates a data set that contains observationwise statistics ALLSTATS requests that all statistics be computed.
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.


Last updated: December 09, 2022