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Parameterizing Models to Test the Hypotheses You Want: Coding Indicator Variables and Modified Continuous Variables

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23 out of 50 users found this white paper useful


Publisher SAS Institute
Publisher Registration N/A
Topics Data Mining - Analysis Date added 09 Mar 2005
Downloads 15 Format 104.0KB PDF

Beginning with Version 8, SAS provides more power and flexibility for categorical variables in the CLASS statement, specifically by allowing the user to specify the method of parameterization and the reference category. The selected parameterization method has a profound effect on how CONTRAST statements are specified and on the interpretation of the parameter estimates and the associated hypothesis tests. An alternative to using the CLASS statement for categorical variables is to code one's own indicator variables, which allows even more control over the parameterization and associated hypotheses. This paper provides a series of examples to allow the reader to become comfortable using the CLASS statement to specify and test desired hypotheses (using the new syntax in PROC LOGISTIC for the examples) and illustrates the corresponding indicator variables.

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