A jackknife variance estimator for unistage stratified samples with unequal probabilities
Berger, Yves G. (2007) A jackknife variance estimator for unistage stratified samples with unequal probabilities. Biometrika, 94, (4), 953-964. (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 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.
|Subjects:||Q Science > QA Mathematics
H Social Sciences > HA Statistics
|Divisions:||University Structure - Pre August 2011 > School of Social Sciences > Social Statistics
|Date Deposited:||18 Jan 2008|
|Last Modified:||02 Mar 2012 12:28|
|Contributors:||Berger, Yves G. (Author)
|Contact Email Address:||Y.G.Berger@soton.ac.uk|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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