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
| CLASS Statement |
The CLASS statement names the classification variables to be used in the model. Typical classification variables are Treatment, Sex, Race, Group, and Replication. If you use the CLASS statement, it must appear before the MODEL statement.
Classification variables can be either character or numeric. By default, class levels are determined from the entire set of formatted values of the CLASS variables.
Note: Prior to SAS 9, class levels were determined by using no more than the first 16 characters of the formatted values. To revert to this previous behavior, you can use the TRUNCATE option in the CLASS statement.
In any case, you can use formats to group values into levels. See the discussion of the FORMAT procedure in the Base SAS Procedures Guide and the discussions of the FORMAT statement and SAS formats in SAS Formats and Informats: Reference. You can adjust the order of CLASS variable levels with the ORDER= option in the PROC GLM statement.
The GLM procedure displays a table summarizing the CLASS variables and their levels, and you can use this to check the ordering of levels and, hence, of the corresponding parameters for main effects. If you need to check the ordering of parameters for interaction effects, use the E option in the MODEL, CONTRAST, ESTIMATE, and LSMEANS statements. See the section Parameterization of PROC GLM Models for more information.
You can specify the following option in the CLASS statement after a slash (/):