Complex Survey Data Analysis with SAS (Paperback, 1)

Features and Examples of Complex SurveysIntroductionDefinitions and Terminology of Sample SurveysOverview of SAS/STAT Procedures Available to Analyze Survey DataFour Features of Complex SurveysExamples of Complex SurveysSummaryDrawing Random Samples Using PROC SURVEYSELECTIntroductionFundamental Sampling TechniquesStatified SamplingCluster Sampling SummaryAnalyzing Continuous Variables Using PROC SURVEYMEANSIntroductionTotalsMeansRatiosQuantilesSummaryAnalyzing Categorical Variables Using PROC SURVEYFREQIntroductionUnivariate AnalysesBivariate AnalysesMultiway TablesSummaryFitting Linear Refression Models Using PROC SURVEYREGIntroductionLinear Regression in a Simple Random Sampling SettingLinear Regression with Complex Survey DataTesting for a Reduced ModelComputing Unit-Level StatisticsSummaryFitting Logistic Regression Models Using PROC SURVERYLOGISTICIntroductionLogistic Regression in a Simple Random Sampling SettingLogistic Regression with Complex Survey DataTesting for a Reduced Model and Adequate Model FitComputing Unit-Level StatisticsCustomizing Odds Ratios Extensions for Modeling Variables with More than Two OutcomesSummarySurvival Analysis with Complex Survey DataIntroductionfoundations of Survival AnalysisSurvival Analysis with Complex Survey DataSummaryDomain EstimationIntroductionDefinitions and an Example Data SetRisk in Subsetting a Complex Survey Data SetDomain Estimation using Domain-Specific WeightsDomain Estimation for Alternative StatisticsSignificance Testing for Domain Mean DifferencesDegress of Freedom AdjustmentsSummaryReplication Techniques for Variance EstimationIntroductionMore Details Regarding Taylor Series LinearizationBalanced Repeated ReplicationFay's Variant to BRRJackknifeBootstrapReplication with Liner ModelsReplication as a Tool for Estimating Variances of Complex Point EstimatesDegrees of Freedom AdjustmentsSummaryWeight Adjustment MethodsIntroductionDefinitions and Missing Data AssumptionsAdjustment Cell MethodPropensity Cell MethodPoststratificationRaking SummaryImputation MethodsIntroductionDefinitions and a Brief Taxonomy of Imputation TechniquesMultiple Imputation as a Way to Incorporate Missing Data UncertaintyUnivariate MissingnessMultivariate MissingnessInferences from Multiply Imputed DataAccounting for Features of the Complex Survey Data during the Imputation Modeling and Analysis StagesSummaryReferencesIndex