Variance estimation for complex surveys using replication techniques

1996/09/01 by KF Rust, Jnk Rao · 4 citations
Mathematics · Social Sciences · #Statistical Methods and Bayesian Inference #Survey Methodology and Nonresponse #Urban, Neighborhood, and Segregation Studies

paper · doi:10.1177/096228029600500305

openalex publication_date 1996/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

The analysis of survey data requires the application of special methods to deal appropriately with the effects of the sample design on the properties of estimators and test statistics. The class of replication techniques represents one approach to handling this problem. This paper discusses the use of these techniques for estimating sampling variances, and the use of such variance estimates in drawing inferences from survey data. The techniques of the jackknife, balanced repeated replication (balanced half-samples), and the bootstrap are described, and the properties of these methods are summarized. Several examples from the literature of the use of replication in analysing large complex surveys are outlined.

Citations

• Resampling Inference with Complex Survey Data

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