A jackknife variance estimator for unistage stratified samples with unequal probabilities


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

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Description/Abstract

Existing jackknife variance estimators used with sample surveys can seriously overestimate the true variance under unistage stratified sampling without replacementwith unequal probabilities.A novel jackknife variance estimator is proposedwhich 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.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1093/biomet/asm072
ISSNs: 0006-3444 (print)
Related URLs:
Keywords: consistency, design-based inference, finite population correction, sample surveys, smooth function of means, stratification
Subjects:
ePrint ID: 44059
Date :
Date Event
12 July 2007Published
Date Deposited: 11 Jul 2007
Last Modified: 16 Apr 2017 18:46
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/44059

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