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The GLM Procedure

Syntax: GLM Procedure

The following statements are available in PROC GLM:

PROC GLM <options> ;
CLASS variables </ option> ;
MODEL dependents=independents </ options> ;
ABSORB variables ;
BY variables ;
FREQ variable ;
ID variables ;
WEIGHT variable ;
CONTRAST ’label’ effect values <...effect values> </ options> ;
ESTIMATE ’label’ effect values <...effect values> </ options> ;
LSMEANS effects </ options> ;
MANOVA <test-options></ detail-options> ;
MEANS effects </ options> ;
OUTPUT <OUT=SAS-data-set> keyword=names <...keyword=names> </ option> ;
RANDOM effects </ options> ;
REPEATED factor-specification </ options> ;
TEST <H=effects> E=effect </ options> ;

Although there are numerous statements and options available in PROC GLM, many applications use only a few of them. Often you can find the features you need by looking at an example or by quickly scanning through this section.

To use PROC GLM, the PROC GLM and MODEL statements are required. You can specify only one MODEL statement (in contrast to the REG procedure, for example, which allows several MODEL statements in the same PROC REG run). If your model contains classification effects, the classification variables must be listed in a CLASS statement, and the CLASS statement must appear before the MODEL statement. In addition, if you use a CONTRAST statement in combination with a MANOVA, RANDOM, REPEATED, or TEST statement, the CONTRAST statement must be entered first in order for the contrast to be included in the MANOVA, RANDOM, REPEATED, or TEST analysis.

Table 39.2 summarizes the positional requirements for the statements in the GLM procedure.

Table 39.2 Positional Requirements for PROC GLM Statements

Statement

 

Must Precede...

 

Must Follow...

ABSORB

 

first RUN statement

   

BY

 

first RUN statement

   

CLASS

 

MODEL statement

   

CONTRAST

 

MANOVA, REPEATED,

 

MODEL statement

   

or RANDOM statement

   

ESTIMATE

     

MODEL statement

FREQ

 

first RUN statement

   

ID

 

first RUN statement

   

LSMEANS

     

MODEL statement

MANOVA

     

CONTRAST or

       

MODEL statement

MEANS

     

MODEL statement

MODEL

 

CONTRAST, ESTIMATE,

 

CLASS statement

   

LSMEANS, or MEANS

   
   

statement

   

OUTPUT

     

MODEL statement

RANDOM

     

CONTRAST or

       

MODEL statement

REPEATED

     

CONTRAST, MODEL,

       

or TEST statement

TEST

 

MANOVA or

 

MODEL statement

   

REPEATED statement

   

WEIGHT

 

first RUN statement

   

Table 39.3 summarizes the function of each statement (other than the PROC statement) in the GLM procedure.

Table 39.3 Statements in the GLM Procedure

Statement

Description

ABSORB

absorbs classification effects in a model

BY

specifies variables to define subgroups for the analysis

CLASS

declares classification variables

CONTRAST

constructs and tests linear functions of the parameters

ESTIMATE

estimates linear functions of the parameters

FREQ

specifies a frequency variable

ID

identifies observations on output

LSMEANS

computes least squares (marginal) means

MANOVA

performs a multivariate analysis of variance

MEANS

computes and optionally compares arithmetic means

MODEL

defines the model to be fit

OUTPUT

requests an output data set containing diagnostics for each observation

RANDOM

declares certain effects to be random and computes expected mean squares

REPEATED

performs multivariate and univariate repeated measures analysis of variance

TEST

constructs tests that use the sums of squares for effects and the error term you specify

WEIGHT

specifies a variable for weighting observations

The rest of this section gives detailed syntax information for each of these statements, beginning with the PROC GLM statement. The remaining statements are covered in alphabetical order.

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