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Frequently Asked Questions

What is Proc surveylogistic used for in SAS?

See Chapter 51, The LOGISTIC Procedure, for general information about how to perform logistic regression by using SAS. PROC SURVEYLOGISTIC is designed to handle sample survey data, and thus it incorporates the sample design information into the analysis.

What are the features of the surveylogistic procedure?

For statistical inferences, PROC SURVEYLOGISTIC incorporates complex survey sample designs, including designs with stratification, clustering, and unequal weighting. The following are highlights of the SURVEYLOGISTIC procedure's features: enables you to import or export SAS data sets containing replicate weights for BRR or jackknife methods

What is selection=score in proclogistic?

For SELECTION=SCORE, PROC LOGISTIC uses the branch-and-bound algorithm of Furnival and Wilson (1974) to find a specified number of models with the highest likelihood score (chi-square) statistic for all possible model sizes, from 1, 2, 3 effect models, and so on, up to the single model containing all of the explanatory effects.

How does Proc surveylogistic exclude an observation from analysis?

By default, PROC SURVEYLOGISTIC completely excludes an observation from analysis if that observation has a missing value, unless you specify the MISSING option. Note that the NOMCAR option has no effect on a classification variable when you specify the MISSING option, which treats missing values as a valid nonmissing level.

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