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Variance estimation for complex surveys using replication techniques

Rust, KF, Rao, Jnk·1996·Statistical Methods in Medical Research

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.

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Metadata

Authors
Rust, K., & Rao, J.
Venue
Statistical Methods in Medical Research
Published
1996-09
Volume
5
Issue
3
Pages
283-310
ISSN
  • 0962-2802 (ISSN-L)
  • 1477-0334
OpenAlex
W2164629226
Cited by
661
References
1
FWCI
3.17
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Variance estimation for complex surveys using replication techniques. https://app.cochat.ai/papers/10.1177/096228029600500305
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Rust, K., & Rao, J. (1996). Variance estimation for complex surveys using replication techniques. Statistical Methods in Medical Research. https://doi.org/10.1177/096228029600500305

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.