Abstract
We first review bootstrap variance estimation for estimators of finite population quantities such as population totals or means. In this context, the bootstrap is typically implemented by producing a set of bootstrap design weights that account for the variability due to sample selection. Sometimes, survey analysts are interested in making inferences about model parameters. We then describe how to modify bootstrap design weights so as to account for the variability resulting from the analyst’s model. Finally, we discuss bootstrap tests of hypotheses for survey data.
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Beaumont, JF. (2014). The Analysis of Survey Data Using the Bootstrap. In: Mecatti, F., Conti, P., Ranalli, M. (eds) Contributions to Sampling Statistics. Contributions to Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-05320-2_4
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DOI: https://doi.org/10.1007/978-3-319-05320-2_4
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