The GLM Procedure
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Overview
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Getting Started
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Syntax
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Details
Statistical Assumptions for Using PROC GLM Specification of Effects Using PROC GLM Interactively Parameterization of PROC GLM Models Hypothesis Testing in PROC GLM Effect Size Measures for F Tests in GLM Absorption Specification of ESTIMATE Expressions Comparing Groups Multivariate Analysis of Variance Repeated Measures Analysis of Variance Random-Effects Analysis Missing Values Computational Resources Computational Method Output Data Sets Displayed Output ODS Table Names ODS Graphics
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Examples
Randomized Complete Blocks with Means Comparisons and Contrasts Regression with Mileage Data Unbalanced ANOVA for Two-Way Design with Interaction Analysis of Covariance Three-Way Analysis of Variance with Contrasts Multivariate Analysis of Variance Repeated Measures Analysis of Variance Mixed Model Analysis of Variance with the RANDOM Statement Analyzing a Doubly Multivariate Repeated Measures Design Testing for Equal Group Variances Analysis of a Screening Design
- References
Weighted Means
In previous releases, if you specified a WEIGHT statement and one or more of the multiple comparisons options, PROC GLM estimated the variance of the difference between weighted group means for group 
and 
as
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where MSE is the (weighted) mean square for error and 
is the size of group . This variance is involved in all of the multiple-comparison methods. Beginning with SAS 6.12, the variance of the difference between weighted group means for group and is computed as
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where 
is the sum of the weights for the observations in group .