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Robust Sample Survey Inference via Bootstrapping and Bias Correction: The Case of the Ratio Estimator

Chambers, R. L. and Dorfman, A. H. (2003) Robust Sample Survey Inference via Bootstrapping and Bias Correction: The Case of the Ratio Estimator , Southampton, UK Southampton Statistical Sciences Research Institute 21pp. (S3RI Methodology Working Papers, M03/13).

Record type: Monograph (Project Report)


The bootstrap approach to statistical inference is described in Efron (1982). The method has wide applicability and has seen considerable development in recent years. However, use of the bootstrap in sample survey inference has been somewhat limited. Rao and Wu (1988), describe an application of the bootstrap under the design-based approach to sample survey inference. Sitter (1992a, 1992b), has extended their results to more complex survey designs. More recently, Booth, Butler and Hall (1991) and Booth and Murison (1992) describe a rather different approach to constructing a design-based bootstrap. In this paper we describe how this approach to the bootstrap can be applied under model-based sample survey inference, focussing on an application where the popular ratio estimator is the estimator of choice.

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Published date: 2003


Local EPrints ID: 8163
PURE UUID: ca3e5349-5ed6-4f1d-a9ee-1bb9728c9a6b

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Date deposited: 11 Jul 2004
Last modified: 17 Jul 2017 17:13

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Author: R. L. Chambers
Author: A. H. Dorfman

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