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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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.
|Keywords:||consistency, design-based inference, finite population correction, sample surveys, smooth function of means, stratification|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||University Structure - Pre August 2011 > Southampton Statistical Sciences Research Institute
|Date Deposited:||11 Jul 2007|
|Last Modified:||04 Apr 2013 09:44|
|Contributors:||Berger, Y.G. (Author)
|Date:||12 July 2007|
|Contact Email Address:||Y.G.Berger@soton.ac.uk|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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