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Bootstrap Variance Estimation for Rejective Sampling
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Journal Article
Bootstrap Variance Estimation for Rejective Sampling
2017
Overview
Replication procedures have proven useful for variance estimation for large scale complex surveys. As an extension of bootstrap procedures to rejective samples, we define a bootstrap sample that is a rejective, unequal probability, replacement sample selected from the original sample. A modification of the bootstrap with improved performance is suggested for stratified samples with small stratum sizes. Simulations for Poisson and stratified rejective samples support the use of replicates in estimating the variance of the regression estimator for rejective samples.
Publisher
Taylor & Francis,Taylor & Francis Ltd
