Transcription of A.1 SAS EXAMPLES
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A.1 SAS EXAMPLES
SAS EXAMPLESSAS is general-purpose software for a wide variety of statistical analyses. The mainprocedures (PROCs) for categorical data analyses are FREQ, GENMOD, LOGISTIC,NLMIXED, GLIMMIX, and CATMOD. PROC FREQ performs basic analyses fortwo-way and three-way contingency tables. PROC GENMOD fits generalized linearmodels using ML or Bayesian methods, cumulative link models for ordinal responses,zero-inflated Poisson regression models for count data, and GEE analyses for marginalmodels. PROC LOGISTIC gives ML fitting of binary response models, cumulative linkmodels for ordinal responses, and baseline-category logit models for nominal responses.(PROC SURVEYLOGISTIC fits binary and multi-category regression models to sur-vey data by incorporating the sample design into the analysis and using the method ofpseudo ML.) PROC CATMOD fits baseline-category logit models and can fit a varietyof other models using weighted least squares.
The examples in this appendix show SAS code for version 9.3. We focus on basic model tting rather than the great variety of options. For more detail, see Stokes, Davis, and Koch (2012) Categorical Data Analysis Using SAS, 3rd ed. Cary, NC: SAS Institute. Allison (2012) Logistic Regression Using SAS: Theory and Application, 2nd edition.
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