The SURVEYLOGISTIC Procedure
- Overview
- Getting Started
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Syntax
PROC SURVEYLOGISTIC StatementBY StatementCLASS StatementCLUSTER StatementCONTRAST StatementDOMAIN StatementEFFECT StatementESTIMATE StatementFREQ StatementLSMEANS StatementLSMESTIMATE StatementMODEL StatementOUTPUT StatementREPWEIGHTS StatementSLICE StatementSTORE StatementSTRATA StatementTEST StatementUNITS StatementWEIGHT Statement -
DetailsMissing ValuesModel SpecificationModel FittingSurvey Design InformationLogistic Regression Models and ParametersVariance EstimationDomain AnalysisHypothesis Testing and EstimationLinear Predictor, Predicted Probability, and Confidence LimitsOutput Data SetsDisplayed OutputODS Table NamesODS Graphics
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Examples
- References
Model Fit Statistics
By default, PROC SURVEYLOGISTIC displays the following information in the “Model Fit Statistics” table:
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“Model Fit Statistics” and “Testing Global Null Hypothesis: BETA=0” tables, which give the various criteria (–2 Log L, AIC, SC) based on the likelihood for fitting a model with intercepts only and for fitting a model with intercepts and explanatory variables. If you specify the NOINT option, these statistics are calculated without considering the intercept parameters. The third column of the table gives the chi-square statistics and p-values for the –2 Log L statistic and for the Score statistic. These test the joint effect of the explanatory variables included in the model. The Score criterion is always missing for the models identified by the first two columns of the table. Note also that the first two rows of the Chi-Square column are always missing, since tests cannot be performed for AIC and SC.
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generalized
measures for the fitted model if you specify the RSQUARE option in the MODEL statement