The CATMOD Procedure
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Overview
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Getting Started
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Syntax
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Details
Missing Values Input Data Sets Ordering of Populations and Responses Specification of Effects Output Data Sets Logistic Analysis Log-Linear Model Analysis Repeated Measures Analysis Generation of the Design Matrix Cautions Computational Method Computational Formulas Memory and Time Requirements Displayed Output ODS Table Names
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Examples
Linear Response Function, r=2 Responses Mean Score Response Function, r=3 Responses Logistic Regression, Standard Response Function Log-Linear Model, Three Dependent Variables Log-Linear Model, Structural and Sampling Zeros Repeated Measures, 2 Response Levels, 3 Populations Repeated Measures, 4 Response Levels, 1 Population Repeated Measures, Logistic Analysis of Growth Curve Repeated Measures, Two Repeated Measurement Factors Direct Input of Response Functions and Covariance Matrix Predicted Probabilities
- References
| LOGLIN Statement |
The LOGLIN statement is used to define log-linear model effects. It can be used whenever the default response functions (generalized logits) are used.
In the LOGLIN statement, effects are design effects that contain dependent variables in the MODEL statement, including interaction, nested, and nested-by-value effects. You can use the bar (|) and at (@) operators as well. The following lists of effects are equivalent:
a b c a*b a*c b*c
and
a|b|c @2
When you use the LOGLIN statement, the keyword _RESPONSE_ should be specified in the MODEL statement. For further information about log-linear model analysis, see the section Log-Linear Model Analysis.
You cannot specify the LOGLIN statement for an analysis that also contains the REPEATED or FACTORS statement since all of them specify the same information: how to partition the variation among the response functions within a population.
You can specify the following option in the LOGLIN statement after a slash.
- TITLE=’title’
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displays the title at the top of certain pages of output that correspond to this LOGLIN statement.
The following statements give an example of how to use the LOGLIN statement:
proc catmod; model a*b*c=_response_; loglin a|b|c @ 2; run;
These statements yield a log-linear model analysis that contains all main effects and two-variable interactions. For more examples of log-linear model analysis, see the section Log-Linear Model Analysis.