The HPMIXED Procedure

OUTPUT Statement

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

The OUTPUT statement creates a data set that contains predicted values and residual diagnostics, computed after fitting the model. By default, all variables in the original data set are included in the output data set.

You can use the ID statement to select a subset of the variables from the input data set to be added to the output data set.

For example, suppose that the data set Scores contains the variables score, machine, and person. The following statements fit a model with fixed machine and random person effects and save the predicted and residual values to the data set igausout:

proc hpmixed data = Scores;
   class machine person score;
   model score = machine;
   random person;
   output out=igausout pred=p resid=r;
run;

You can specify the following options in the OUTPUT statement before the slash (/).

OUT=SAS data set

specifies the name of the output data set. If the OUT= option is omitted, the procedure uses the DATAn convention to name the output data set.

keyword <(keyword-options)><=name>

specifies a statistic to include in the output data set and optionally assigns the variable the name name. You can use the keyword-options to control which type of a particular statistic to compute. The keyword-options can take on the following values:

BLUP: uses the predictors of the random effects in computing the statistic.
NOBLUP: does not use the predictors of the random effects in computing the statistic.

The default is to compute statistics by using BLUPs. For example, the following two OUTPUT statements are equivalent:

output out=out1  pred=predicted lcl=lower;
output out=out1  pred(blup)=predicted lcl(blup)=lower;

If a particular combination of keyword and keyword-options is not supported, the statistic is not computed and a message is produced in the SAS log.

A keyword can appear multiple times in the OUTPUT statement. Table 48.7 lists the keywords and the default names assigned by the HPMIXED procedure if you do not specify a name. In this table, y denotes the response variable.

Table 48.7: Keywords for Output Statistics

Keyword	Options	Description	Expression	Name
PREDICTED	BLUP	Linear predictor	$\widehat{\eta } = \mb {x}’\widehat{\bbeta }+\mb {z}’\widehat{\bgamma }$	Pred
	NOBLUP	Marginal linear predictor	$\widehat{\eta }_ m = \mb {x}’\widehat{\bbeta }$	PredPA
STDERR	BLUP	Standard deviation of linear predictor	$\sqrt {\mr {Var}[\widehat{\eta }-\mb {z}’\bgamma ]}$	StdErr
	NOBLUP	Standard deviation of marginal linear predictor	$\sqrt {\mr {Var}[\widehat{\eta }_ m]}$	StdErrPA
RESIDUAL	BLUP	Residual	$r = y - \widehat{\eta }$	Resid
	NOBLUP	Marginal residual	$r_ m = y - \widehat{\eta }_ m$	ResidPA
PEARSON	BLUP	Pearson-type residual	$r / \sqrt {\widehat{\mr {Var}}[y\|\bgamma ]}$	Pearson
	NOBLUP	Marginal Pearson-type residual	$r_ m / \sqrt {\widehat{\mr {Var}}[y]}$	PearsonPA
STUDENT	BLUP	Studentized residual	$r / \sqrt {\widehat{\mr {Var}}[r]}$	Student
	NOBLUP	Studentized marginal residual	$r_ m / \sqrt {\widehat{\mr {Var}}[r_ m]}$	StudentPA
LCL	BLUP	Lower prediction limit for linear predictor		LCL
	NOBLUP	Lower confidence limit for marginal linear predictor		LCLPA
UCL	BLUP	Upper prediction limit for linear predictor		UCL
	NOBLUP	Upper confidence limit for marginal linear predictor		UCLPA
VARIANCE	BLUP	Conditional variance of response variable	$\widehat{\mr {Var}}[y\|\bgamma ]$	Variance
	NOBLUP	Marginal variance of response variable	$\widehat{\mr {Var}}[y]$	VariancePA

You can use the following shortcuts to request statistics: PRED for PREDICTED, STD for STDERR, RESID for RESIDUAL, VAR for VARIANCE.

You can specify the following options of the OUTPUT statement after the slash (/).

ALLSTATS

requests that all statistics are computed. If you do not use a keyword to assign a name, the HPMIXED procedure uses the default name.

ALPHA=number

determines the coverage probability for two-sided confidence and prediction intervals. The coverage probability is computed as $1-\mr {\Argument{number}}$ . The value of number must be between 0 and 1 inclusively; the default is 0.05.

NOMISS

requests that records from the input data set be written to the output data only for those observations that were used in the analysis. By default, the HPMIXED procedure produces output statistics for all observations in the input data set.

NOUNIQUE

requests that names not be made unique in the case of naming conflicts. By default, the HPMIXED procedure avoids naming conflicts by assigning a unique name to each output variable. If you specify the NOUNIQUE option, variables with conflicting names are not renamed. In that case, the first variable added to the output data set takes precedence.

NOVAR

requests that variables from the input data set not be added to the output data set. This option ignores ID statement but does not apply to variables listed in a BY statement.