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A jackknife variance estimator for unistage stratified samples with unequal probabilities

Record type: Article

Existing jackknife variance estimators used with sample surveys can seriously overestimate the true variance under unistage stratified sampling without replacement with unequal probabilities. A novel jackknife variance estimator is proposed which is as numerically simple as existing jackknife variance estimators. Under certain regularity conditions, the proposed variance estimator is consistent under stratified sampling without replacement with unequal probabilities. The high entropy regularity condition necessary for consistency is shown to hold for the Rao–Sampford design. An empirical study of three unequal probability sampling designs supports our findings.

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Citation

Berger, Y.G. (2007) A jackknife variance estimator for unistage stratified samples with unequal probabilities Biometrika, 94, (4), pp. 953-964. (doi:10.1093/biomet/asm072).

More information

Published date: 12 July 2007
Keywords: consistency, design-based inference, finite population correction, sample surveys, smooth function of means, stratification
Organisations: Southampton Statistical Research Inst.

Identifiers

Local EPrints ID: 34543
URI: http://eprints.soton.ac.uk/id/eprint/34543
ISSN: 0006-3444
PURE UUID: c099f411-592e-49c4-b832-9ae1b6afe306

Catalogue record

Date deposited: 18 Jan 2008
Last modified: 17 Jul 2017 15:50

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