Includes bibliographical references (p. 83-87) and index.

Introduction -- Sample design and survey data -- Types of sampling -- The nature of survey data -- A different view of survey data -- Complexity of analyzing survey data -- Adjusting for differential representation: the weight -- Developing the weight by poststratification -- Adjusting the weight in a followup survey -- Assessing the loss or gain in precision: the design effect -- The use of sample weights for survey data analysis -- Strategies for variance estimation -- Replicated sampling: a general approach -- Balanced repeated replication -- Jackknife repeated replication -- The bootstrap method -- The Taylor series method (linearization) -- Preparing for survey data analysis -- Data requirements for survey analysis -- Importance of preliminary analysis -- Choices of the method for variance estimation -- Available computing resources -- Creating replicate weights -- Searching for appropriate models for survey data analysis -- Conducting survey data analysis -- A strategy for conducting preliminary analysis -- Conducting descriptive analysis -- Conducting linear regression analysis -- Conducting contingency table analysis -- Conducting logistic regression analysis -- Other logistic regression models -- Design-based and model-based analysis* -- Concluding remarks.