GLM Procedure
The GLM procedure uses the method of least squares to fit general linear models.
Among the statistical methods available in PROC GLM are regression, analysis of variance,
analysis of covariance, multivariate analysis of variance, and partial correlation.
The following are highlights of the procedure's features:
 enables you to specify any degree of interaction (crossed effects) and nested effects
 enables you to specify polynomial, continuousbyclass, and continuousnesting class effects
 enables you to absorb classification effects in a model
 enables you to specify random effects in a model
 produces expected mean squares for each Type I, Type II, Type III, Type IV, and contrast mean squares used in the analysis
 enables you to specify both hypothesis effects and the error effect to use for a multivariate analysis of variance
 performs BY group processing, which enables you to obtain separate analyses on grouped observations
 computes least square means and least square mean differences for classification effects
 performs multiple comparison adjustments for the pvalues and confidence limits for the least square mean differences
 computes arithmetic means and standard deviations of all continuous variables in a model within each group corresponding to each effect

 performs multiple comparison of main effect means
 tests hypotheses for the effects of a linear model regardless of the number of missing cells or the extent of confounding
 performs F tests that use appropriate mean squares or linear combinations of mean squares as error terms
 estimates linear functions of the model parameters
 tests hypotheses for linear combinations of the model parameters
 displays the sum of squares associated with each hypothesis tested and, upon request, the form of the estimable function employed in a test.
 produces the general form of all estimable functions
 creates an output data set that contains the input data set, predicted values, residuals, and other diagnostic measures
 creates a SAS data set that corresponds to any output table
 automatically creates graphs by using ODS Graphics

For further details see the GLM Procedure
Examples