The authors begin by reviewing common types of survey sample designs and demystifying sampling weights by explaining what they are, and how they are developed and adjusted. They then carefully discuss the major issues of variance estimation and of preliminary as well as multivariate analysis of complex cross-sectional survey data when sampling weights are taken into account. They focus on the design-based approach that directly engages sample designs in the analysis (although they also discuss the model-based perspective, which can augment a design-based approach in some analysis), and they illustrate the approach with popular software examples. Students of survey analysis will find the text of great use in their efforts in making sample-based statistical inferences.
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