Bootstrap methods for analyzing complex sample survey data
|Product:||Statistics Canada International Symposium Series: Proceedings|
Application of standard methods to survey data without accounting for the design features and weight adjustments can lead to erroneous inferences. Bootstrap methods offer an attractive option to the analyst for taking account of the design features and weight adjustments. The data file consists of the full-sample final weights and associated bootstrap final weights for a large number of bootstrap replicates as well as the observed data on the sample elements. We show how such data files can be used to analyze survey data in a straightforward manner using weighted estimating equations. A one-step estimating function bootstrap method that avoids some difficulties with the bootstrap is also discussed.
bootstrap statistics, estimation methods, models, regression analysis, survey methodology, survey sampling.
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