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Features and Examples of Complex Surveys Introduction Definitions and Terminology of Sample Surveys Overview of SAS/STAT Procedures Available to Analyze Survey Data Four Features of Complex Surveys Examples of Complex Surveys Summary Drawing Random Samples Using PROC SURVEYSELECT Introduction Fundamental Sampling Techniques Statified Sampling Cluster Sampling Summary Analyzing Continuous Variables Using PROC SURVEYMEANS Introduction Totals Means Ratios Quantiles Summary Analyzing Categorical Variables Using PROC SURVEYFREQ Introduction Univariate Analyses Bivariate Analyses Multiway Tables Summary Fitting Linear Refression Models Using PROC SURVEYREG Introduction Linear Regression in a Simple Random Sampling Setting Linear Regression with Complex Survey Data Testing for a Reduced Model Computing Unit-Level Statistics Summary Fitting Logistic Regression Models Using PROC SURVERYLOGISTIC Introduction Logistic Regression in a Simple Random Sampling Setting Logistic Regression with Complex Survey Data Testing for a Reduced Model and Adequate Model Fit Computing Unit-Level Statistics Customizing Odds Ratios Extensions for Modeling Variables with More than Two Outcomes Summary Survival Analysis with Complex Survey Data Introduction foundations of Survival Analysis Survival Analysis with Complex Survey Data Summary Domain Estimation Introduction Definitions and an Example Data Set Risk in Subsetting a Complex Survey Data Set Domain Estimation using Domain-Specific Weights Domain Estimation for Alternative Statistics Significance Testing for Domain Mean Differences Degress of Freedom Adjustments Summary Replication Techniques for Variance Estimation Introduction More Details Regarding Taylor Series Linearization Balanced Repeated Replication Fay's Variant to BRR Jackknife Bootstrap Replication with Liner Models Replication as a Tool for Estimating Variances of Complex Point Estimates Degrees of Freedom Adjustments Summary Weight Adjustment Methods Introduction Definitions and Missing Data Assumptions Adjustment Cell Method Propensity Cell Method Poststratification Raking Summary Imputation Methods Introduction Definitions and a Brief Taxonomy of Imputation Techniques Multiple Imputation as a Way to Incorporate Missing Data Uncertainty Univariate Missingness Multivariate Missingness Inferences from Multiply Imputed Data Accounting for Features of the Complex Survey Data during the Imputation Modeling and Analysis Stages Summary References Index