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 9.1 summarizes the basic functions and important options of the PROC HPLMIXED statements. The syntax of each statement in Table 9.1 is described in the following sections in alphabetical order after the description of the PROC HPLMIXED statement.

Table 9.1: 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 $\mb{X}$ and $\mb{Z}$ matrices.

None

ID

Lists additional variables to be included in predicted values tables

None

MODEL

Specifies dependent variable and fixed effects, setting up $\mb{X}$

S requests a solution for fixed-effects parameters.

RANDOM

Specifies random effects, setting up $\mb{Z}$ and $\mb{G}$

SUBJECT= creates block-diagonality; TYPE= specifies the covariance structure; S requests a solution for the random effects.

REPEATED

Sets up $\mb{R}$

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.

PERFORMANCE

Invokes the distributed computing connection

NODES= specifies the number of nodes to use.